Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDFeiping Nie 0001
Person information
- affiliation: Northwestern Polytechnical University, School of Computer Science, OPTIMAL, Xi'an, China
- affiliation (2009 - 2015): University of Texas at Arlington, TX, USA
- affiliation (PhD 2009): Tsinghua University, Beijing, China
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j429]Ruihan Chen
, Junpeng Tan, Yinghong Zhou, Zhijing Yang, Feiping Nie, Tianshui Chen:
Asymmetric low-rank double-level cooperation for scalable discrete cross-modal hashing. Expert Syst. Appl. 237(Part C): 121703 (2024)- [j428]Han Zhang, Maoguo Gong, Yannian Gu, Feiping Nie, Xuelong Li:
Side-constrained graph fusion for semi-supervised multi-view clustering. Neurocomputing 570: 127102 (2024) - [j427]Ben Yang, Zhiyuan Xue, Jinghan Wu, Xuetao Zhang, Feiping Nie, Badong Chen:
Anchor-graph regularized orthogonal concept factorization for document clustering. Neurocomputing 573: 127173 (2024) - [j426]Ben Yang, Jinghan Wu, Xuetao Zhang, Xinhu Zheng, Feiping Nie, Badong Chen:
Discrete correntropy-based multi-view anchor-graph clustering. Inf. Fusion 103: 102097 (2024) - [j425]Yunzhi Ling, Feiping Nie, Weizhong Yu, Yunhao Ling, Xuelong Li:
Robust autoencoder feature selector for unsupervised feature selection. Inf. Sci. 660: 120121 (2024) - [j424]Zheng Wang, Feiping Nie, Canyu Zhang, Rong Wang, Xuelong Li:
Worst-Case Discriminative Feature Learning via Max-Min Ratio Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 46(1): 641-658 (2024) - [j423]Feiping Nie, Jitao Lu, Danyang Wu, Rong Wang, Xuelong Li:
A Novel Normalized-Cut Solver With Nearest Neighbor Hierarchical Initialization. IEEE Trans. Pattern Anal. Mach. Intell. 46(1): 659-666 (2024) - [j422]Feiping Nie, Jingjing Xue, Weizhong Yu, Xuelong Li:
Fast Clustering With Anchor Guidance. IEEE Trans. Pattern Anal. Mach. Intell. 46(4): 1898-1912 (2024) - [j421]Jikui Wang, Yiwen Wu, Bing Li, Zhenguo Yang, Feiping Nie:
Fast anchor graph preserving projections. Pattern Recognit. 146: 109996 (2024) - [j420]Quan Wang, Fei Wang, Zhongheng Li, Zheng Wang, Feiping Nie:
Coordinate Descent Optimized Trace Difference Model for Joint Clustering and Feature Extraction. Pattern Recognit. 146: 110062 (2024) - [j419]Zequn Yang, Han Zhang, Yake Wei, Zheng Wang, Feiping Nie, Di Hu:
Geometric-inspired graph-based Incomplete Multi-view Clustering. Pattern Recognit. 147: 110082 (2024) - [j418]Zhengxin Li, Feiping Nie, Danyang Wu, Zheng Wang, Xuelong Li:
Sparse Trace Ratio LDA for Supervised Feature Selection. IEEE Trans. Cybern. 54(4): 2420-2433 (2024) - [j417]Jingyu Wang, Shengzhao Guo, Feiping Nie, Xuelong Li:
Local-Global Fuzzy Clustering With Anchor Graph. IEEE Trans. Fuzzy Syst. 32(1): 188-202 (2024) - [j416]Weizhong Yu, Liyin Xing, Feiping Nie, Xuelong Li:
Multiview Fuzzy Clustering Based on Anchor Graph. IEEE Trans. Fuzzy Syst. 32(3): 755-766 (2024) - [j415]Zhezheng Hao, Zhoumin Lu, Guoxu Li, Feiping Nie, Rong Wang, Xuelong Li:
Ensemble Clustering With Attentional Representation. IEEE Trans. Knowl. Data Eng. 36(2): 581-593 (2024) - [j414]Sisi Wang, Feiping Nie, Zheng Wang, Rong Wang, Xuelong Li:
Outliers Robust Unsupervised Feature Selection for Structured Sparse Subspace. IEEE Trans. Knowl. Data Eng. 36(3): 1234-1248 (2024) - [j413]Jitao Lu, Feiping Nie, Xia Dong, Rong Wang, Xuelong Li:
Bidirectional Attentive Multi-View Clustering. IEEE Trans. Knowl. Data Eng. 36(5): 1889-1901 (2024) - [j412]Hong Chen, Feiping Nie, Rong Wang, Xuelong Li:
Unsupervised Feature Selection With Flexible Optimal Graph. IEEE Trans. Neural Networks Learn. Syst. 35(2): 2014-2027 (2024) - [j411]Jintang Bian, Dandan Zhao, Feiping Nie, Rong Wang, Xuelong Li:
Robust and Sparse Principal Component Analysis With Adaptive Loss Minimization for Feature Selection. IEEE Trans. Neural Networks Learn. Syst. 35(3): 3601-3614 (2024) - [j410]Feiping Nie, Hong Chen, Shiming Xiang, Changshui Zhang, Shuicheng Yan, Xuelong Li:
On the Equivalence of Linear Discriminant Analysis and Least Squares Regression. IEEE Trans. Neural Networks Learn. Syst. 35(4): 5710-5720 (2024) - [c226]Feiping Nie, Zhezheng Hao, Rong Wang:
Multi-Class Support Vector Machine with Maximizing Minimum Margin. AAAI 2024: 14466-14473 - [i48]Xueyuan Xu, Fulin Wei, Tianyuan Jia, Li Zhuo, Feiping Nie, Xia Wu:
Embedded Multi-label Feature Selection via Orthogonal Regression. CoRR abs/2403.00307 (2024) - [i47]Danyang Wu, Xinjie Shen, Jitao Lu, Jin Xu, Feiping Nie:
Simple Multigraph Convolution Networks. CoRR abs/2403.05014 (2024) - 2023
- [j409]He Xiong, Deguang Kong, Feiping Nie:
Cauchy balanced nonnegative matrix factorization. Artif. Intell. Rev. 56(10): 11867-11903 (2023) - [j408]Zhengguo Yang, Jikui Wang, Qiang Li, Jihai Yi, Xuewen Liu, Feiping Nie:
Graph optimization for unsupervised dimensionality reduction with probabilistic neighbors. Appl. Intell. 53(2): 2348-2361 (2023) - [j407]Xiaojun Yang, Junhong Gong, Lianpei Wu, Zhijing Yang, Yukai Shi, Feiping Nie:
Reference-free low-light image enhancement by associating hierarchical wavelet representations. Expert Syst. Appl. 213(Part C): 118920 (2023) - [j406]Sisi Wang, Feiping Nie, Zheng Wang, Rong Wang, Xuelong Li:
Max-Min Robust Principal Component Analysis. Neurocomputing 521: 89-98 (2023) - [j405]Ben Yang, Jinghan Wu, Xuetao Zhang, Zhiping Lin, Feiping Nie, Badong Chen:
Robust anchor-based multi-view clustering via spectral embedded concept factorization. Neurocomputing 528: 136-147 (2023) - [j404]Jianyong Zhu, Jingwei Chen, Bin Xu, Hui Yang, Feiping Nie:
Fast orthogonal locality-preserving projections for unsupervised feature selection. Neurocomputing 531: 100-113 (2023) - [j403]Jingyu Wang, Hongmei Wang, Feiping Nie, Xuelong Li:
Feature selection with multi-class logistic regression. Neurocomputing 543: 126268 (2023) - [j402]Qianyao Qiang, Bin Zhang, Feiping Nie, Fei Wang:
Multi-view semi-supervised learning with adaptive graph fusion. Neurocomputing 557: 126685 (2023) - [j401]Jingyu Wang, Xinru Zhang, Feiping Nie, Xuelong Li:
Enhanced Robust Fuzzy K-Means Clustering joint ℓ0-norm constraint. Neurocomputing 561: 126842 (2023) - [j400]Sisi Wang, Feiping Nie, Zheng Wang, Rong Wang, Xuelong Li:
Sparse robust subspace learning via boolean weight. Inf. Fusion 96: 224-236 (2023) - [j399]Muhammad Adnan Ashraf, Rao Muhammad Adeel Nawab, Feiping Nie:
Tran-Switch: A transfer learning approach for sentence level cross-genre author profiling on code-switched English-RomanUrdu Text. Inf. Process. Manag. 60(3): 103261 (2023) - [j398]Bing Li, Jikui Wang, Zhengguo Yang, Jihai Yi, Feiping Nie:
Fast semi-supervised self-training algorithm based on data editing. Inf. Sci. 626: 293-314 (2023) - [j397]Wei Chang, Feiping Nie, Rong Wang, Xuelong Li:
Calibrated multi-task subspace learning via binary group structure constraint. Inf. Sci. 631: 271-287 (2023) - [j396]Mingyu Zhao, Weidong Yang, Feiping Nie:
Auto-weighted orthogonal and nonnegative graph reconstruction for multi-view clustering. Inf. Sci. 632: 324-339 (2023) - [j395]Quan Wang, Fei Wang, Zhongheng Li, Peilin Jiang, Fuji Ren, Feiping Nie:
Efficient random subspace decision forests with a simple probability dimensionality setting scheme. Inf. Sci. 638: 118993 (2023) - [j394]Xiaojun Yang, Mingjun Zhu, Yongda Cai, Zheng Wang, Feiping Nie:
Fast spectral clustering with self-adapted bipartite graph learning. Inf. Sci. 644: 118810 (2023) - [j393]Qiang Chen, Weizhong Yu, Xiaowei Zhao, Feiping Nie, Xuelong Li:
Rooted Mahalanobis distance based Gustafson-Kessel fuzzy C-means. Inf. Sci. 644: 118878 (2023) - [j392]Mingyu Zhao, Weidong Yang, Feiping Nie:
MVCformer: A transformer-based multi-view clustering method. Inf. Sci. 649: 119622 (2023) - [j391]Xiaowei Zhao, Feiping Nie, Weizhong Yu, Xuelong Li:
Fast neighborhood reconstruction with adaptive weights learning. Knowl. Based Syst. 259: 110082 (2023) - [j390]Weizhong Yu, Liyin Xing, Feiping Nie, Xuelong Li:
An efficient semi-supervised balanced cut with hard pairwise constraints and partial labels. Knowl. Based Syst. 276: 110747 (2023) - [j389]Zhanxuan Hu, Yichen Wang, Hailong Ning, Danyang Wu, Feiping Nie:
Mutual-Taught Deep Clustering. Knowl. Based Syst. 282: 111100 (2023) - [j388]Xiaojun Yang, Mingjun Zhu, Bo Sun, Zheng Wang, Feiping Nie:
Fuzzy C-Multiple-Means Clustering for Hyperspectral Image. IEEE Geosci. Remote. Sens. Lett. 20: 1-5 (2023) - [j387]Jikui Wang, Yiwen Wu, Shaobo Li, Feiping Nie:
A self-training algorithm based on the two-stage data editing method with mass-based dissimilarity. Neural Networks 168: 431-449 (2023) - [j386]Mingyu Zhao, Weidong Yang, Feiping Nie:
Deep graph reconstruction for multi-view clustering. Neural Networks 168: 560-568 (2023) - [j385]Shenfei Pei, Huimin Chen, Feiping Nie, Rong Wang, Xuelong Li:
Centerless Clustering. IEEE Trans. Pattern Anal. Mach. Intell. 45(1): 167-181 (2023) - [j384]Feiping Nie, Lai Tian, Rong Wang, Xuelong Li:
Learning Feature-Sparse Principal Subspace. IEEE Trans. Pattern Anal. Mach. Intell. 45(4): 4858-4869 (2023) - [j383]Zhengxin Li, Feiping Nie, Jintang Bian, Danyang Wu, Xuelong Li:
Sparse PCA via $\ell _{2,p}$ℓ2,p-Norm Regularization for Unsupervised Feature Selection. IEEE Trans. Pattern Anal. Mach. Intell. 45(4): 5322-5328 (2023) - [j382]Zhoumin Lu, Feiping Nie, Rong Wang, Xuelong Li:
A Differentiable Perspective for Multi-View Spectral Clustering With Flexible Extension. IEEE Trans. Pattern Anal. Mach. Intell. 45(6): 7087-7098 (2023) - [j381]Han Zhang, Feiping Nie, Xuelong Li:
Large-Scale Clustering With Structured Optimal Bipartite Graph. IEEE Trans. Pattern Anal. Mach. Intell. 45(8): 9950-9963 (2023) - [j380]Rong Wang, Huimin Chen, Yihang Lu, Qianrong Zhang, Feiping Nie, Xuelong Li:
Discrete and Balanced Spectral Clustering With Scalability. IEEE Trans. Pattern Anal. Mach. Intell. 45(12): 14321-14336 (2023) - [j379]Qianyao Qiang, Bin Zhang, Fei Wang, Feiping Nie:
Multi-View Discrete Clustering: A Concise Model. IEEE Trans. Pattern Anal. Mach. Intell. 45(12): 15154-15170 (2023) - [j378]Zhoumin Lu, Shiping Wang, Genggeng Liu, Feiping Nie:
Robust weighted co-clustering with global and local discrimination. Pattern Recognit. 138: 109405 (2023) - [j377]Jingyu Wang, Hongmei Wang, Feiping Nie, Xuelong Li:
Sparse feature selection via fast embedding spectral analysis. Pattern Recognit. 139: 109472 (2023) - [j376]Wei Chang, Feiping Nie, Rong Wang, Xuelong Li:
Elaborate multi-task subspace learning with discrete group constraint. Pattern Recognit. 139: 109515 (2023) - [j375]Ziheng Li, Feiping Nie, Rong Wang, Xuelong Li:
Robust rank-one matrix completion with rank estimation. Pattern Recognit. 142: 109637 (2023) - [j374]Zheng Wang, Qi Li, Haifeng Zhao, Feiping Nie:
Simultaneous local clustering and unsupervised feature selection via strong space constraint. Pattern Recognit. 142: 109718 (2023) - [j373]Mingyu Zhao, Weidong Yang, Feiping Nie:
Deep multi-view spectral clustering via ensemble. Pattern Recognit. 144: 109836 (2023) - [j372]Jingyu Wang, Yidi Wang, Feiping Nie, Xuelong Li:
Discriminative projection fuzzy K-Means with adaptive neighbors. Pattern Recognit. Lett. 176: 21-27 (2023) - [j371]Yihang Lu, Xuan Zheng, Haonan Xin, Haoliang Tang, Rong Wang, Feiping Nie:
Ensemble and random collaborative representation-based anomaly detector for hyperspectral imagery. Signal Process. 204: 108835 (2023) - [j370]Haonan Xin, Yihang Lu, Haoliang Tang, Rong Wang, Feiping Nie:
Self-Weighted Euler $k$-Means Clustering. IEEE Signal Process. Lett. 30: 1127-1131 (2023) - [j369]Huafeng Li, Minghui Liu, Zhanxuan Hu, Feiping Nie, Zhengtao Yu:
Intermediary-Guided Bidirectional Spatial-Temporal Aggregation Network for Video-Based Visible-Infrared Person Re-Identification. IEEE Trans. Circuits Syst. Video Technol. 33(9): 4962-4972 (2023) - [j368]Feiping Nie, Wei Chang, Rong Wang, Xuelong Li:
Learning an Optimal Bipartite Graph for Subspace Clustering via Constrained Laplacian Rank. IEEE Trans. Cybern. 53(2): 1235-1247 (2023) - [j367]Zhengxin Li, Feiping Nie, Danyang Wu, Zhanxuan Hu, Xuelong Li:
Unsupervised Feature Selection With Weighted and Projected Adaptive Neighbors. IEEE Trans. Cybern. 53(2): 1260-1271 (2023) - [j366]Feiping Nie, Xiaowei Zhao, Rong Wang, Xuelong Li:
Adaptive Maximum Entropy Graph-Guided Fast Locality Discriminant Analysis. IEEE Trans. Cybern. 53(6): 3574-3587 (2023) - [j365]Yong Peng, Keding Chen, Feiping Nie, Bao-Liang Lu, Wanzeng Kong:
Two-Dimensional Embedded Fuzzy Data Clustering. IEEE Trans. Emerg. Top. Comput. Intell. 7(4): 1263-1275 (2023) - [j364]Yong Peng, Wenna Huang, Wanzeng Kong, Feiping Nie, Bao-Liang Lu:
JGSED: An End-to-End Spectral Clustering Model for Joint Graph Construction, Spectral Embedding and Discretization. IEEE Trans. Emerg. Top. Comput. Intell. 7(6): 1687-1701 (2023) - [j363]Chaodie Liu, Feiping Nie, Rong Wang, Xuelong Li:
Graph-Based Soft-Balanced Fuzzy Clustering. IEEE Trans. Fuzzy Syst. 31(6): 2044-2055 (2023) - [j362]Jingwei Chen, Jianyong Zhu, Hongyun Jiang, Hui Yang, Feiping Nie:
Sparsity Fuzzy C-Means Clustering With Principal Component Analysis Embedding. IEEE Trans. Fuzzy Syst. 31(7): 2099-2111 (2023) - [j361]Qiang Chen, Feiping Nie, Weizhong Yu, Xuelong Li:
$\ell _{2,p}$-Norm and Mahalanobis Distance-Based Robust Fuzzy C-Means. IEEE Trans. Fuzzy Syst. 31(9): 2904-2916 (2023) - [j360]Jianyong Zhu, Wenjie Zhao, Hui Yang, Feiping Nie:
Joint Learning of Anchor Graph-Based Fuzzy Spectral Embedding and Fuzzy K-Means. IEEE Trans. Fuzzy Syst. 31(11): 4097-4108 (2023) - [j359]Yong Peng, Honggang Liu, Wanzeng Kong, Feiping Nie, Bao-Liang Lu, Andrzej Cichocki:
Joint EEG Feature Transfer and Semisupervised Cross-Subject Emotion Recognition. IEEE Trans. Ind. Informatics 19(7): 8104-8115 (2023) - [j358]Shaojun Shi, Feiping Nie, Rong Wang, Xuelong Li:
Fast Multi-View Clustering via Prototype Graph. IEEE Trans. Knowl. Data Eng. 35(1): 443-455 (2023) - [j357]Zhen Wang, Xiangfeng Dai, Peican Zhu, Rong Wang, Xuelong Li, Feiping Nie:
Fast Optimization of Spectral Embedding and Improved Spectral Rotation. IEEE Trans. Knowl. Data Eng. 35(2): 1515-1527 (2023) - [j356]Yunlong Gao, Tingting Lin, Yisong Zhang, Sizhe Luo, Feiping Nie:
Robust Principal Component Analysis Based on Discriminant Information. IEEE Trans. Knowl. Data Eng. 35(2): 1991-2003 (2023) - [j355]Xiaowei Zhao, Feiping Nie, Rong Wang, Xuelong Li:
Robust Fuzzy K-Means Clustering With Shrunk Patterns Learning. IEEE Trans. Knowl. Data Eng. 35(3): 3001-3013 (2023) - [j354]Jianyong Zhu, Lihong Tao, Hui Yang, Feiping Nie:
Unsupervised Optimized Bipartite Graph Embedding. IEEE Trans. Knowl. Data Eng. 35(3): 3224-3238 (2023) - [j353]Feiping Nie, Ziheng Li, Rong Wang, Xuelong Li:
An Effective and Efficient Algorithm for K-Means Clustering With New Formulation. IEEE Trans. Knowl. Data Eng. 35(4): 3433-3443 (2023) - [j352]Quan Wang, Fei Wang, Fuji Ren, Zhongheng Li, Feiping Nie:
An Effective Clustering Optimization Method for Unsupervised Linear Discriminant Analysis. IEEE Trans. Knowl. Data Eng. 35(4): 3444-3457 (2023) - [j351]Hong Chen, Feiping Nie, Rong Wang, Xuelong Li:
Fast Unsupervised Feature Selection With Bipartite Graph and $\ell _{2,0}$ℓ2,0-Norm Constraint. IEEE Trans. Knowl. Data Eng. 35(5): 4781-4793 (2023) - [j350]Zhen Wang, Long Zhang, Rong Wang, Feiping Nie, Xuelong Li:
Semi-Supervised Learning via Bipartite Graph Construction With Adaptive Neighbors. IEEE Trans. Knowl. Data Eng. 35(5): 5257-5268 (2023) - [j349]Rong Wang, Canyu Zhang, Jintang Bian, Zheng Wang, Feiping Nie, Xuelong Li:
Sparse and Flexible Projections for Unsupervised Feature Selection. IEEE Trans. Knowl. Data Eng. 35(6): 6362-6375 (2023) - [j348]Ben Yang, Xuetao Zhang, Zhongheng Li, Feiping Nie, Fei Wang:
Efficient Multi-View K-Means Clustering With Multiple Anchor Graphs. IEEE Trans. Knowl. Data Eng. 35(7): 6887-6900 (2023) - [j347]Feiping Nie, Zhanxuan Hu, Xiaoqian Wang, Xuelong Li, Heng Huang:
Iteratively Re-Weighted Method for Sparsity-Inducing Norms. IEEE Trans. Knowl. Data Eng. 35(7): 7045-7055 (2023) - [j346]Jingjing Xue, Feiping Nie, Rong Wang, Xuelong Li:
Rank-$r$r Discrete Matrix Factorization for Anchor Graph Clustering. IEEE Trans. Knowl. Data Eng. 35(7): 7371-7381 (2023) - [j345]Danyang Wu, Feiping Nie, Jitao Lu, Rong Wang, Xuelong Li:
Effective Clustering via Structured Graph Learning. IEEE Trans. Knowl. Data Eng. 35(8): 7909-7920 (2023) - [j344]Chaodie Liu, Feiping Nie, Rong Wang, Xuelong Li:
Scalable Fuzzy Clustering With Anchor Graph. IEEE Trans. Knowl. Data Eng. 35(8): 8503-8514 (2023) - [j343]Jianyong Zhu, Xinyun Chen, Hui Yang, Feiping Nie:
Unsupervised Adaptive Bipartite Graph Embedding. IEEE Trans. Knowl. Data Eng. 35(10): 10514-10525 (2023) - [j342]Di Hu, Zheng Wang, Feiping Nie, Rong Wang, Xuelong Li:
Self-Supervised Learning for Heterogeneous Audiovisual Scene Analysis. IEEE Trans. Multim. 25: 3534-3545 (2023) - [j341]Shaojun Shi, Feiping Nie, Rong Wang, Xuelong Li:
Multi-View Clustering via Nonnegative and Orthogonal Graph Reconstruction. IEEE Trans. Neural Networks Learn. Syst. 34(1): 201-214 (2023) - [j340]Wei Wang, Haojie Li, Zhengming Ding, Feiping Nie, Junyang Chen, Xiao Dong, Zhihui Wang:
Rethinking Maximum Mean Discrepancy for Visual Domain Adaptation. IEEE Trans. Neural Networks Learn. Syst. 34(1): 264-277 (2023) - [j339]Weizhong Yu, Jintang Bian, Feiping Nie, Rong Wang, Xuelong Li:
Unsupervised Subspace Learning With Flexible Neighboring. IEEE Trans. Neural Networks Learn. Syst. 34(4): 2043-2056 (2023) - [j338]Xiaowei Zhao, Feiping Nie, Rong Wang, Xuelong Li:
Joint Dynamic Manifold and Discriminant Information Learning for Feature Extraction. IEEE Trans. Neural Networks Learn. Syst. 34(6): 2753-2766 (2023) - [j337]Jingyu Wang, Lin Wang, Feiping Nie, Xuelong Li:
Joint Feature Selection and Extraction With Sparse Unsupervised Projection. IEEE Trans. Neural Networks Learn. Syst. 34(6): 3071-3081 (2023) - [j336]Feiping Nie, Shaojun Shi, Jing Li, Xuelong Li:
Implicit Weight Learning for Multi-View Clustering. IEEE Trans. Neural Networks Learn. Syst. 34(8): 4223-4236 (2023) - [j335]Wei Chang, Feiping Nie, Yijie Zhi, Rong Wang, Xuelong Li:
Multitask Learning for Classification Problem via New Tight Relaxation of Rank Minimization. IEEE Trans. Neural Networks Learn. Syst. 34(9): 6055-6068 (2023) - [j334]Ben Yang, Xuetao Zhang, Feiping Nie, Badong Chen, Fei Wang, Zhixiong Nan, Nanning Zheng:
ECCA: Efficient Correntropy-Based Clustering Algorithm With Orthogonal Concept Factorization. IEEE Trans. Neural Networks Learn. Syst. 34(10): 7377-7390 (2023) - [j333]Jingyu Wang, Fangyuan Xie, Feiping Nie, Xuelong Li:
Robust Supervised and Semisupervised Least Squares Regression Using ℓ2,p-Norm Minimization. IEEE Trans. Neural Networks Learn. Syst. 34(11): 8389-8403 (2023) - [j332]Feiping Nie, Sisi Wang, Zheng Wang, Rong Wang, Xuelong Li:
Discrete Robust Principal Component Analysis via Binary Weights Self-Learning. IEEE Trans. Neural Networks Learn. Syst. 34(11): 9064-9077 (2023) - [j331]Feiping Nie, Xia Dong, Zhanxuan Hu, Rong Wang, Xuelong Li:
Discriminative Projected Clustering via Unsupervised LDA. IEEE Trans. Neural Networks Learn. Syst. 34(11): 9466-9480 (2023) - [j330]Feiping Nie, Canyu Zhang, Zheng Wang, Rong Wang, Xuelong Li:
Local Embedding Learning via Landmark-Based Dynamic Connections. IEEE Trans. Neural Networks Learn. Syst. 34(11): 9481-9492 (2023) - [j329]Rong Wang, Jintang Bian, Feiping Nie, Xuelong Li:
Nonlinear Feature Selection Neural Network via Structured Sparse Regularization. IEEE Trans. Neural Networks Learn. Syst. 34(11): 9493-9505 (2023) - [c225]Lei Xu, Rong Wang, Feiping Nie, Xuelong Li:
Efficient Top-K Feature Selection Using Coordinate Descent Method. AAAI 2023: 10594-10601 - [c224]Zhezheng Hao, Zhoumin Lu, Feiping Nie, Rong Wang, Xuelong Li:
Multi-View K-Means with Laplacian Embedding. ICASSP 2023: 1-5 - [c223]Yongjin Yuan, Zheng Wang, Feiping Nie, Xuelong Li:
Unsupervised Feature Selection with self-Weighted and ℓ2,0-Norm Constraint. ICASSP 2023: 1-5 - [c222]Han Zhang, Maoguo Gong, Feiping Nie, Xuelong Li:
Multilayer Subspace Learning With Self-Sparse Robustness for Two-Dimensional Feature Extraction. ICASSP 2023: 1-5 - [c221]Lei Xu, Rong Wang, Feiping Nie, Jun Wu, Xuelong Li:
Semi-Supervised Top-k Feature Selection with a General Optimization Framework. ICME 2023: 288-293 - [c220]Penglei Wang, Danyang Wu, Rong Wang, Feiping Nie:
Multi-view Graph Clustering via Efficient Global-Local Spectral Embedding Fusion. ACM Multimedia 2023: 3268-3276 - [c219]Lei Xu, Lei Chen, Rong Wang, Feiping Nie, Xuelong Li:
Joint Feature and Differentiable k-NN Graph Learning using Dirichlet Energy. NeurIPS 2023 - [c218]Mingyu Zhao, Weidong Yang, Feiping Nie:
Transformer-Based Contrastive Multi-view Clustering via Ensembles. ECML/PKDD (1) 2023: 678-694 - [i46]Bo Jiang, Fei Xu, Ziyan Zhang, Jin Tang, Feiping Nie:
AGFormer: Efficient Graph Representation with Anchor-Graph Transformer. CoRR abs/2305.07521 (2023) - [i45]Lei Xu, Lei Chen, Rong Wang, Feiping Nie, Xuelong Li:
Joint Feature and Differentiable k-NN Graph Learning using Dirichlet Energy. CoRR abs/2305.12396 (2023) - [i44]Xinjie Shen, Danyang Wu, Jitao Lu, Junjie Liang, Jin Xu, Feiping Nie:
NP2L: Negative Pseudo Partial Labels Extraction for Graph Neural Networks. CoRR abs/2310.01098 (2023) - [i43]Feiping Nie, Jitao Lu, Danyang Wu, Rong Wang, Xuelong Li:
A Novel Normalized-Cut Solver with Nearest Neighbor Hierarchical Initialization. CoRR abs/2311.15214 (2023) - [i42]Feiping Nie, Zhezheng Hao, Rong Wang:
Multi-class Support Vector Machine with Maximizing Minimum Margin. CoRR abs/2312.06578 (2023) - 2022
- [j328]Haifeng Zhao, Qi Li, Zheng Wang, Feiping Nie:
Joint Adaptive Graph Learning and Discriminative Analysis for Unsupervised Feature Selection. Cogn. Comput. 14(3): 1211-1221 (2022) - [j327]Ziheng Li, Zhanxuan Hu, Feiping Nie, Rong Wang, Xuelong Li:
Multi-view clustering based on generalized low rank approximation. Neurocomputing 471: 251-259 (2022) - [j326]Shaojun Shi, Feiping Nie, Rong Wang, Xuelong Li:
Semi-supervised learning based on intra-view heterogeneity and inter-view compatibility for image classification. Neurocomputing 488: 248-260 (2022) - [j325]Shaojun Shi, Feiping Nie, Rong Wang, Xuelong Li:
When multi-view classification meets ensemble learning. Neurocomputing 490: 17-29 (2022) - [j324]Xiaowei Zhao, Feiping Nie, Rong Wang, Xuelong Li:
Improving projected fuzzy K-means clustering via robust learning. Neurocomputing 491: 34-43 (2022) - [j323]Qianyao Qiang, Bin Zhang, Fei Wang, Feiping Nie:
Multi-view unsupervised dimensionality reduction with probabilistic neighbors. Neurocomputing 500: 203-216 (2022) - [j322]Han Zhang, Maoguo Gong, Feiping Nie, Xuelong Li:
Unified dual-label semi-supervised learning with top-k feature selection. Neurocomputing 501: 875-888 (2022) - [j321]Xiaojun Yang, Siyuan Li, Ke Liang, Feiping Nie, Liang Lin:
Structured graph optimization for joint spectral embedding and clustering. Neurocomputing 503: 62-72 (2022) - [j320]Zheng Wang, Haojie Hu, Rong Wang, Qianrong Zhang, Feiping Nie, Xuelong Li:
Capped ℓp-norm linear discriminant analysis for robust projections learning. Neurocomputing 511: 399-409 (2022) - [j319]Jikui Wang, Zhengguo Yang, Xuewen Liu, Bing Li, Jihai Yi, Feiping Nie:
Projected fuzzy C-means with probabilistic neighbors. Inf. Sci. 607: 553-571 (2022) - [j318]Xia Dong, Danyang Wu, Feiping Nie, Rong Wang, Xuelong Li:
Multi-view clustering with adaptive procrustes on Grassmann manifold. Inf. Sci. 609: 855-875 (2022) - [j317]Canyu Zhang, Feiping Nie, Rong Wang, Xuelong Li:
Fast unsupervised embedding learning with anchor-based graph. Inf. Sci. 609: 949-962 (2022) - [j316]Jingwei Chen, Jianyong Zhu, Bingxia Feng, Shiyu Xie, Hui Yang, Feiping Nie:
A novel method for optimizing spectral rotation embedding K-means with coordinate descent. Inf. Sci. 612: 1095-1110 (2022) - [j315]Jingwei Chen, Jianyong Zhu, Shiyu Xie, Hui Yang, Feiping Nie:
FGC_SS: Fast Graph Clustering Method by Joint Spectral Embedding and Improved Spectral Rotation. Inf. Sci. 613: 853-870 (2022) - [j314]Danyang Wu, Han Wang, Zhanxuan Hu, Feiping Nie:
Improved deep metric learning with local neighborhood component analysis. Inf. Sci. 617: 165-176 (2022) - [j313]Chenhui Gao, Wenzhi Chen, Feiping Nie, Weizhong Yu, Feihu Yan:
Subspace clustering by directly solving Discriminative K-means. Knowl. Based Syst. 252: 109452 (2022) - [j312]Xiaojun Yang, Guoquan Lin, Yijun Liu, Feiping Nie, Liang Lin:
Fast Spectral Embedded Clustering Based on Structured Graph Learning for Large-Scale Hyperspectral Image. IEEE Geosci. Remote. Sens. Lett. 19: 1-5 (2022) - [j311]Lei Xu, Hui Wu, Chunming He, Jun Wang, Changqing Zhang, Feiping Nie, Lei Chen:
Multi-modal sequence learning for Alzheimer's disease progression prediction with incomplete variable-length longitudinal data. Medical Image Anal. 82: 102643 (2022) - [j310]Ben Yang, Xuetao Zhang, Badong Chen, Feiping Nie, Zhiping Lin, Zhixiong Nan:
Efficient correntropy-based multi-view clustering with anchor graph embedding. Neural Networks 146: 290-302 (2022) - [j309]Siyuan Peng, Zhijing Yang, Feiping Nie, Badong Chen, Zhiping Lin:
Correntropy based semi-supervised concept factorization with adaptive neighbors for clustering. Neural Networks 154: 203-217 (2022) - [j308]Shenfei Pei, Yuze Zhang, Rong Wang, Feiping Nie:
A portable clustering algorithm based on compact neighbors for face tagging. Neural Networks 154: 508-520 (2022) - [j307]Xuelong Li, Han Zhang, Rong Wang, Feiping Nie:
Multiview Clustering: A Scalable and Parameter-Free Bipartite Graph Fusion Method. IEEE Trans. Pattern Anal. Mach. Intell. 44(1): 330-344 (2022) - [j306]Feiping Nie, Danyang Wu, Rong Wang, Xuelong Li:
Truncated Robust Principle Component Analysis With A General Optimization Framework. IEEE Trans. Pattern Anal. Mach. Intell. 44(2): 1081-1097 (2022) - [j305]Feiping Nie, Jingjing Xue, Danyang Wu, Rong Wang, Hui Li, Xuelong Li:
Coordinate Descent Method for $k$k-means. IEEE Trans. Pattern Anal. Mach. Intell. 44(5): 2371-2385 (2022) - [j304]Kun Song, Junwei Han, Gong Cheng, Jiwen Lu, Feiping Nie:
Adaptive Neighborhood Metric Learning. IEEE Trans. Pattern Anal. Mach. Intell. 44(9): 4591-4604 (2022) - [j303]Feiping Nie, Xiaowei Zhao, Rong Wang, Xuelong Li:
Fast Locality Discriminant Analysis With Adaptive Manifold Embedding. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 9315-9330 (2022) - [j302]Jingyu Wang, Hongmei Wang, Feiping Nie, Xuelong Li:
Ratio Sum Versus Sum Ratio for Linear Discriminant Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 10171-10185 (2022) - [j301]Shaojun Shi, Feiping Nie, Rong Wang, Xuelong Li:
Self-weighting multi-view spectral clustering based on nuclear norm. Pattern Recognit. 124: 108429 (2022) - [j300]Jingyu Wang, Zhenyu Ma, Feiping Nie, Xuelong Li:
Entropy regularization for unsupervised clustering with adaptive neighbors. Pattern Recognit. 125: 108517 (2022) - [j299]Danyang Wu, Wei Chang, Jitao Lu, Feiping Nie, Rong Wang, Xuelong Li:
Adaptive-order proximity learning for graph-based clustering. Pattern Recognit. 126: 108550 (2022) - [j298]Danyang Wu, Xia Dong, Feiping Nie, Rong Wang, Xuelong Li:
An attention-based framework for multi-view clustering on Grassmann manifold. Pattern Recognit. 128: 108610 (2022) - [j297]Wei Chang, Feiping Nie, Zheng Wang, Rong Wang, Xuelong Li:
Self-weighted learning framework for adaptive locality discriminant analysis. Pattern Recognit. 129: 108778 (2022) - [j296]Chen Wang, Xiaojun Chen, Feiping Nie, Joshua Zhexue Huang:
Directly solving normalized cut for multi-view data. Pattern Recognit. 130: 108809 (2022) - [j295]Huimin Chen, Qianrong Zhang, Rong Wang, Feiping Nie, Xuelong Li:
A general soft-balanced clustering framework based on a novel balance regularizer. Signal Process. 198: 108572 (2022) - [j294]Qiang Chen, Xiaowei Zhao, Feiping Nie, Rong Wang, Xuelong Li:
Fast Adaptive Local Subspace Learning With Regressive Regularization. IEEE Signal Process. Lett. 29: 1759-1763 (2022) - [j293]Yong Peng, Wenjuan Wang, Wanzeng Kong, Feiping Nie, Bao-Liang Lu, Andrzej Cichocki:
Joint Feature Adaptation and Graph Adaptive Label Propagation for Cross-Subject Emotion Recognition From EEG Signals. IEEE Trans. Affect. Comput. 13(4): 1941-1958 (2022) - [j292]Danyang Wu, Feiping Nie, Jitao Lu, Rong Wang, Xuelong Li:
Balanced Graph Cut With Exponential Inter-Cluster Compactness. IEEE Trans. Artif. Intell. 3(4): 498-505 (2022) - [j291]Yong Peng, Feiwei Qin, Wanzeng Kong, Yuan Ge, Feiping Nie, Andrzej Cichocki:
GFIL: A Unified Framework for the Importance Analysis of Features, Frequency Bands, and Channels in EEG-Based Emotion Recognition. IEEE Trans. Cogn. Dev. Syst. 14(3): 935-947 (2022) - [j290]Wei Wang, Baopu Li, Mengzhu Wang, Feiping Nie, Zhihui Wang, Haojie Li:
Confidence Regularized Label Propagation Based Domain Adaptation. IEEE Trans. Circuits Syst. Video Technol. 32(6): 3319-3333 (2022) - [j289]Ben Yang, Xuetao Zhang, Zhiping Lin, Feiping Nie, Badong Chen, Fei Wang:
Efficient and Robust MultiView Clustering With Anchor Graph Regularization. IEEE Trans. Circuits Syst. Video Technol. 32(9): 6200-6213 (2022) - [j288]Feiping Nie, Zheng Wang, Lai Tian, Rong Wang, Xuelong Li:
Subspace Sparse Discriminative Feature Selection. IEEE Trans. Cybern. 52(6): 4221-4233 (2022) - [j287]Xiaojun Chen, Renjie Chen, Qingyao Wu, Feiping Nie, Min Yang, Rui Mao:
Semisupervised Feature Selection via Structured Manifold Learning. IEEE Trans. Cybern. 52(7): 5756-5766 (2022) - [j286]Xuelong Li, Qi Wang, Feiping Nie, Mulin Chen:
Locality Adaptive Discriminant Analysis Framework. IEEE Trans. Cybern. 52(8): 7291-7302 (2022) - [j285]Chen Wang, Xiaojun Chen, Guowen Yuan, Feiping Nie, Min Yang:
Semisupervised Feature Selection With Sparse Discriminative Least Squares Regression. IEEE Trans. Cybern. 52(8): 8413-8424 (2022) - [j284]Jingyu Wang, Zhenyu Ma, Feiping Nie, Xuelong Li:
Progressive Self-Supervised Clustering With Novel Category Discovery. IEEE Trans. Cybern. 52(10): 10393-10406 (2022) - [j283]Feiping Nie, Ziheng Li, Zhanxuan Hu, Rong Wang, Xuelong Li:
Robust Matrix Completion With Column Outliers. IEEE Trans. Cybern. 52(11): 12042-12055 (2022) - [j282]Feiping Nie, Chaodie Liu, Rong Wang, Zhen Wang, Xuelong Li:
Fast Fuzzy Clustering Based on Anchor Graph. IEEE Trans. Fuzzy Syst. 30(7): 2375-2387 (2022) - [j281]Jingjing Xue, Feiping Nie, Rong Wang, Xuelong Li:
Iteratively Reweighted Algorithm for Fuzzy $c$-Means. IEEE Trans. Fuzzy Syst. 30(10): 4310-4321 (2022) - [j280]Yong Peng, Yikai Zhang, Wanzeng Kong, Feiping Nie, Bao-Liang Lu, Andrzej Cichocki:
S3LRR: A Unified Model for Joint Discriminative Subspace Identification and Semisupervised EEG Emotion Recognition. IEEE Trans. Instrum. Meas. 71: 1-13 (2022) - [j279]Yikai Zhang, Ruiqi Guo, Yong Peng, Wanzeng Kong, Feiping Nie, Bao-Liang Lu:
An Auto-Weighting Incremental Random Vector Functional Link Network for EEG-Based Driving Fatigue Detection. IEEE Trans. Instrum. Meas. 71: 1-14 (2022) - [j278]Rong Wang, Jitao Lu, Yihang Lu, Feiping Nie, Xuelong Li:
Discrete and Parameter-Free Multiple Kernel k-Means. IEEE Trans. Image Process. 31: 2796-2808 (2022) - [j277]Ben Yang, Xuetao Zhang, Feiping Nie, Fei Wang:
Fast Multiview Clustering With Spectral Embedding. IEEE Trans. Image Process. 31: 3884-3895 (2022) - [j276]Yunlong Gao, Tingting Lin, Jinyan Pan, Feiping Nie, Youwei Xie:
Fuzzy Sparse Deviation Regularized Robust Principal Component Analysis. IEEE Trans. Image Process. 31: 5645-5660 (2022) - [j275]Bin Zhang, Qianyao Qiang, Fei Wang, Feiping Nie:
Fast Multi-View Semi-Supervised Learning With Learned Graph. IEEE Trans. Knowl. Data Eng. 34(1): 286-299 (2022) - [j274]Junwei Han, Jinglin Xu, Feiping Nie, Xuelong Li:
Multi-View K-Means Clustering With Adaptive Sparse Memberships and Weight Allocation. IEEE Trans. Knowl. Data Eng. 34(2): 816-827 (2022) - [j273]Rong Wang, Jintang Bian, Feiping Nie, Xuelong Li:
Unsupervised Discriminative Projection for Feature Selection. IEEE Trans. Knowl. Data Eng. 34(2): 942-953 (2022) - [j272]Feiping Nie, Xiaowei Zhao, Rong Wang, Xuelong Li, Zhihui Li:
Fuzzy K-Means Clustering With Discriminative Embedding. IEEE Trans. Knowl. Data Eng. 34(3): 1221-1230 (2022) - [j271]Feiping Nie, Wei Chang, Zhanxuan Hu, Xuelong Li:
Robust Subspace Clustering With Low-Rank Structure Constraint. IEEE Trans. Knowl. Data Eng. 34(3): 1404-1415 (2022) - [j270]Feiping Nie, Wei Zhu, Xuelong Li:
Unsupervised Large Graph Embedding Based on Balanced and Hierarchical K-Means. IEEE Trans. Knowl. Data Eng. 34(4): 2008-2019 (2022) - [j269]Feiping Nie, Zheng Wang, Rong Wang, Xuelong Li:
Adaptive Local Embedding Learning for Semi-Supervised Dimensionality Reduction. IEEE Trans. Knowl. Data Eng. 34(10): 4609-4621 (2022) - [j268]Shuangyan Yi, Feiping Nie, Yongsheng Liang, Wei Liu, Zhenyu He, Qingmin Liao:
Fast Extended Inductive Robust Principal Component Analysis With Optimal Mean. IEEE Trans. Knowl. Data Eng. 34(10): 4812-4825 (2022) - [j267]Xueyuan Xu, Xia Wu, Fulin Wei, Wei Zhong, Feiping Nie:
A General Framework for Feature Selection Under Orthogonal Regression With Global Redundancy Minimization. IEEE Trans. Knowl. Data Eng. 34(11): 5056-5069 (2022) - [j266]Feiping Nie, Xia Dong, Lai Tian, Rong Wang, Xuelong Li:
Unsupervised Feature Selection With Constrained ℓ₂, ₀-Norm and Optimized Graph. IEEE Trans. Neural Networks Learn. Syst. 33(4): 1702-1713 (2022) - [j265]Zhe Liu, Yun Li, Lina Yao, Xianzhi Wang, Feiping Nie:
Agglomerative Neural Networks for Multiview Clustering. IEEE Trans. Neural Networks Learn. Syst. 33(7): 2842-2852 (2022) - [j264]Jingyu Wang, Lin Wang, Feiping Nie, Xuelong Li:
Fast Unsupervised Projection for Large-Scale Data. IEEE Trans. Neural Networks Learn. Syst. 33(8): 3634-3644 (2022) - [j263]Jingyu Wang, Zhenyu Ma, Feiping Nie, Xuelong Li:
Fast Self-Supervised Clustering With Anchor Graph. IEEE Trans. Neural Networks Learn. Syst. 33(9): 4199-4212 (2022) - [j262]Jingyu Wang, Lin Wang, Feiping Nie, Xuelong Li:
A Novel Formulation of Trace Ratio Linear Discriminant Analysis. IEEE Trans. Neural Networks Learn. Syst. 33(10): 5568-5578 (2022) - [j261]Jingyu Wang, Fangyuan Xie, Feiping Nie, Xuelong Li:
Unsupervised Adaptive Embedding for Dimensionality Reduction. IEEE Trans. Neural Networks Learn. Syst. 33(11): 6844-6855 (2022) - [j260]Danyang Wu, Feiping Nie, Xia Dong, Rong Wang, Xuelong Li:
Parameter-Free Consensus Embedding Learning for Multiview Graph-Based Clustering. IEEE Trans. Neural Networks Learn. Syst. 33(12): 7944-7950 (2022) - [j259]Chen Zhao, Wu Gao, Feiping Nie, Huiyang Zhou:
A Survey of GPU Multitasking Methods Supported by Hardware Architecture. IEEE Trans. Parallel Distributed Syst. 33(6): 1451-1463 (2022) - [c217]Yihang Lu, Haonan Xin, Rong Wang, Feiping Nie, Xuelong Li:
Scalable Multiple Kernel k-means Clustering. CIKM 2022: 4279-4283 - [c216]Yihang Lu, Xuan Zheng, Jitao Lu, Rong Wang, Feiping Nie, Xuelong Li:
Self-Paced and Discrete Multiple Kernel k-Means. CIKM 2022: 4284-4288 - [c215]Jitao Lu, Yihang Lu, Rong Wang, Feiping Nie, Xuelong Li:
Multiple Kernel K-Means Clustering with Simultaneous Spectral Rotation. ICASSP 2022: 4143-4147 - [c214]Yihang Lu, Jitao Lu, Rong Wang, Feiping Nie:
Discrete Multi-Kernel K-Means with Diverse and Optimal Kernel Learning. ICASSP 2022: 4153-4157 - [c213]Yihang Lu, Xuan Zheng, Rong Wang, Feiping Nie, Xuelong Li:
A Unified Framework for Discrete Multi-kernel k-means with Kernel Diversity Regularization. ICPR 2022: 4934-4940 - [c212]Danyang Wu, Jitao Lu, Feiping Nie, Rong Wang, Yuan Yuan:
EMGC²F: Efficient Multi-view Graph Clustering with Comprehensive Fusion. IJCAI 2022: 3566-3572 - [i41]Kun Song, Junwei Han, Gong Cheng, Jiwen Lu, Feiping Nie:
Adaptive neighborhood Metric learning. CoRR abs/2201.08314 (2022) - [i40]Junyun Cui, Xiaoyu Shen, Feiping Nie, Zheng Wang, Jinglong Wang, Yulong Chen:
A Survey on Legal Judgment Prediction: Datasets, Metrics, Models and Challenges. CoRR abs/2204.04859 (2022) - [i39]Liangchen Liu, Qiuhong Ke, Chaojie Li, Feiping Nie, Yingying Zhu:
Unified Multi-View Orthonormal Non-Negative Graph Based Clustering Framework. CoRR abs/2211.02883 (2022) - [i38]Feiping Nie, Hong Chen, Rong Wang, Xuelong Li:
On the Global Solution of Soft k-Means. CoRR abs/2212.03589 (2022) - 2021
- [j258]Yuan Yuan, Xin Li, Qi Wang, Feiping Nie:
A semi-supervised learning algorithm via adaptive Laplacian graph. Neurocomputing 426: 162-173 (2021) - [j257]Zhiwei Xing, Yingcang Ma, Xiaofei Yang, Feiping Nie:
Graph regularized nonnegative matrix factorization with label discrimination for data clustering. Neurocomputing 440: 297-309 (2021) - [j256]Danyang Wu, Zhanxuan Hu, Feiping Nie, Rong Wang, Hui Yang, Xuelong Li:
Multi-view clustering with interactive mechanism. Neurocomputing 449: 378-388 (2021) - [j255]Rongxiu Lu, Yingjie Cai, Jianyong Zhu, Feiping Nie, Hui Yang:
Dimension reduction of multimodal data by auto-weighted local discriminant analysis. Neurocomputing 461: 27-40 (2021) - [j254]Shenfei Pei, Feiping Nie, Rong Wang, Xuelong Li:
An Efficient Density-based clustering algorithm for face groping. Neurocomputing 462: 331-343 (2021) - [j253]Han Zhang, Danyang Wu, Feiping Nie, Rong Wang, Xuelong Li:
Multilevel projections with adaptive neighbor graph for unsupervised multi-view feature selection. Inf. Fusion 70: 129-140 (2021) - [j252]Weichan Zhong, Xiaojun Chen, Feiping Nie, Joshua Zhexue Huang:
Adaptive discriminant analysis for semi-supervised feature selection. Inf. Sci. 566: 178-194 (2021) - [j251]Yong Peng, Xin Zhu, Feiping Nie, Wanzeng Kong, Yuan Ge:
Fuzzy graph clustering. Inf. Sci. 571: 38-49 (2021) - [j250]Ziheng Li, Zhanxuan Hu, Feiping Nie, Rong Wang, Xuelong Li:
Matrix completion with column outliers and sparse noise. Inf. Sci. 573: 125-140 (2021) - [j249]Canyu Zhang, Feiping Nie, Zheng Wang, Rong Wang, Xuelong Li:
Fast local representation learning via adaptive anchor graph for image retrieval. Inf. Sci. 578: 870-886 (2021) - [j248]Zhanxuan Hu, Shuzheng Hao, Feiping Nie, Rong Wang, Xuelong Li:
Learning to hash based on angularly discriminative embedding. Inf. Sci. 579: 541-552 (2021) - [j247]Chen Wang, Xiaojun Chen, Bingkun Chen, Feiping Nie, Bo Wang, Zhong Ming:
Learning unsupervised node representation from multi-view network. Inf. Sci. 579: 700-716 (2021) - [j246]Zhanxuan Hu, Danyang Wu, Feiping Nie, Rong Wang:
Generalization bottleneck in deep metric learning. Inf. Sci. 581: 249-261 (2021) - [j245]Ke Liang, Xiaojun Yang, Yuxiong Xu, Rong Wang, Feiping Nie:
Ratio sum formula for dimensionality reduction. Multim. Tools Appl. 80(3): 4367-4382 (2021) - [j244]Zhanxuan Hu, Feiping Nie, Rong Wang, Xuelong Li:
Low Rank Regularization: A review. Neural Networks 136: 218-232 (2021) - [j243]Zhongheng Li, Qianyao Qiang, Bin Zhang, Fei Wang, Feiping Nie:
Flexible multi-view semi-supervised learning with unified graph. Neural Networks 142: 92-104 (2021) - [j242]Feiping Nie, Zheng Wang, Rong Wang, Zhen Wang, Xuelong Li:
Towards Robust Discriminative Projections Learning via Non-Greedy $\ell _{2, 1}$ℓ2, 1-Norm MinMax. IEEE Trans. Pattern Anal. Mach. Intell. 43(6): 2086-2100 (2021) - [j241]Zhen Wang, Zhaoqing Li, Rong Wang, Feiping Nie, Xuelong Li:
Large Graph Clustering With Simultaneous Spectral Embedding and Discretization. IEEE Trans. Pattern Anal. Mach. Intell. 43(12): 4426-4440 (2021) - [j240]Kun Song, Xiwen Yao, Feiping Nie, Xuelong Li, Mingliang Xu:
Weighted bilateral K-means algorithm for fast co-clustering and fast spectral clustering. Pattern Recognit. 109: 107560 (2021) - [j239]Zheng Wang, Feiping Nie, Rong Wang, Hui Yang, Xuelong Li:
Local structured feature learning with dynamic maximum entropy graph. Pattern Recognit. 111: 107673 (2021) - [j238]Lixiang Xu, Lixin Cui, Thomas Weise, Xinlu Li, Zhize Wu, Feiping Nie, Enhong Chen, Yuanyan Tang:
Semi-supervised multi-Layer convolution kernel learning in credit evaluation. Pattern Recognit. 120: 108125 (2021) - [j237]Zheng Wang, Feiping Nie, Canyu Zhang, Rong Wang, Xuelong Li:
Joint nonlinear feature selection and continuous values regression network. Pattern Recognit. Lett. 150: 197-206 (2021) - [j236]Danyang Wu, Shenfei Pei, Feiping Nie, Rong Wang, Xuelong Li:
Multi-Directional Multi-Label Learning. Signal Process. 187: 108143 (2021) - [j235]Ziheng Li, Danyang Wu, Feiping Nie, Rong Wang, Zhensheng Sun, Xuelong Li:
Multi-View Clustering Based on Invisible Weights. IEEE Signal Process. Lett. 28: 1051-1055 (2021) - [j234]Hong Chen, Feiping Nie, Rong Wang, Xuelong Li:
Adaptive Flexible Optimal Graph for Unsupervised Dimensionality Reduction. IEEE Signal Process. Lett. 28: 2162-2166 (2021) - [j233]Fang He, Feiping Nie, Rong Wang, Weimin Jia, Fenggan Zhang, Xuelong Li:
Semisupervised Band Selection With Graph Optimization for Hyperspectral Image Classification. IEEE Trans. Geosci. Remote. Sens. 59(12): 10298-10311 (2021) - [j232]Qi Wang, Zequn Qin, Feiping Nie, Xuelong Li:
C2DNDA: A Deep Framework for Nonlinear Dimensionality Reduction. IEEE Trans. Ind. Electron. 68(2): 1684-1694 (2021) - [j231]Yong Peng, Wanzeng Kong, Feiwei Qin, Feiping Nie, Jinglong Fang, Bao-Liang Lu, Andrzej Cichocki:
Self-Weighted Semi-Supervised Classification for Joint EEG-Based Emotion Recognition and Affective Activation Patterns Mining. IEEE Trans. Instrum. Meas. 70: 1-11 (2021) - [j230]Ben Yang, Xuetao Zhang, Feiping Nie, Fei Wang, Weizhong Yu, Rong Wang:
Fast Multi-View Clustering via Nonnegative and Orthogonal Factorization. IEEE Trans. Image Process. 30: 2575-2586 (2021) - [j229]Bin Zhang, Qianyao Qiang, Fei Wang, Feiping Nie:
Flexible Multi-View Unsupervised Graph Embedding. IEEE Trans. Image Process. 30: 4143-4156 (2021) - [j228]Feiping Nie, Lai Tian, Heng Huang, Chris Ding:
Non-Greedy L21-Norm Maximization for Principal Component Analysis. IEEE Trans. Image Process. 30: 5277-5286 (2021) - [j227]Xiaojun Chen, Yuzhong Ye, Qingyao Wu, Feiping Nie:
Fast Manifold Ranking With Local Bipartite Graph. IEEE Trans. Image Process. 30: 6744-6756 (2021) - [j226]Caixia Yan, Xiaojun Chang, Minnan Luo, Qinghua Zheng, Xiaoqin Zhang, Zhihui Li, Feiping Nie:
Self-weighted Robust LDA for Multiclass Classification with Edge Classes. ACM Trans. Intell. Syst. Technol. 12(1): 4:1-4:19 (2021) - [j225]Feiping Nie, Wei Zhu, Xuelong Li:
Structured Graph Optimization for Unsupervised Feature Selection. IEEE Trans. Knowl. Data Eng. 33(3): 1210-1222 (2021) - [j224]Fei Wang, Quan Wang, Feiping Nie, Zhongheng Li, Weizhong Yu, Rong Wang:
Unsupervised Linear Discriminant Analysis for Jointly Clustering and Subspace Learning. IEEE Trans. Knowl. Data Eng. 33(3): 1276-1290 (2021) - [j223]Junwei Han, Kai Xiong, Feiping Nie, Xuelong Li:
Structured Graph Reconstruction for Scalable Clustering. IEEE Trans. Knowl. Data Eng. 33(5): 2252-2265 (2021) - [j222]Fang He, Feiping Nie, Rong Wang, Haojie Hu, Weimin Jia, Xuelong Li:
Fast Semi-Supervised Learning With Optimal Bipartite Graph. IEEE Trans. Knowl. Data Eng. 33(9): 3245-3257 (2021) - [j221]Lyujian Lu, Saad Elbeleidy, Lauren Zoe Baker, Hua Wang, Feiping Nie:
Predicting Cognitive Declines Using Longitudinally Enriched Representations for Imaging Biomarkers. IEEE Trans. Medical Imaging 40(3): 891-904 (2021) - [j220]Chen Zhao, Wu Gao, Feiping Nie:
A Resource-Efficient Parallel Connected Component Labeling Algorithm and Its Hardware Implementation. IEEE Trans. Multim. 23: 4184-4197 (2021) - [j219]Feiping Nie, Xia Dong, Xuelong Li:
Unsupervised and Semisupervised Projection With Graph Optimization. IEEE Trans. Neural Networks Learn. Syst. 32(4): 1547-1559 (2021) - [j218]Xia Wu, Xueyuan Xu, Jianhong Liu, Hailing Wang, Bin Hu, Feiping Nie:
Supervised Feature Selection With Orthogonal Regression and Feature Weighting. IEEE Trans. Neural Networks Learn. Syst. 32(5): 1831-1838 (2021) - [c211]Hoon Seo, Lodewijk Brand, Hua Wang, Feiping Nie:
Integrating Static and Dynamic Data for Improved Prediction of Cognitive Declines Using Augmented Genotype-Phenotype Representations. AAAI 2021: 522-530 - [c210]Qianyao Qiang, Bin Zhang, Fei Wang, Feiping Nie:
Fast Multi-view Discrete Clustering with Anchor Graphs. AAAI 2021: 9360-9367 - [c209]Wei Chang, Feiping Nie, Rong Wang, Xuelong Li:
New Tight Relaxations of Rank Minimization for Multi-Task Learning. CIKM 2021: 2910-2914 - [c208]Shenfei Pei, Feiping Nie, Rong Wang, Xuelong Li:
A Rank-Constrained Clustering Algorithm with Adaptive Embedding. ICASSP 2021: 2845-2849 - [c207]Feiping Nie, Wei Chang, Xuelong Li, Jin Xu, Gongfu Li:
Adaptive Feature Weight Learning For Robust Clustering Problem with Sparse Constraint. ICASSP 2021: 3125-3129 - [c206]Canyu Zhang, Feiping Nie, Zheng Wang, Rong Wang, Xuelong Li:
Fast Local Representation Learning with Adaptive Anchor Graph. ICASSP 2021: 3170-3174 - [c205]Xia Dong, Danyang Wu, Feiping Nie, Rong Wang, Xuelong Li:
Dependence-Guided Multi-View Clustering. ICASSP 2021: 3650-3654 - [c204]Xiaoqian Wang, Feiping Nie:
Multi-Task Learning Via Sharing Inexact Low-Rank Subspace. ICASSP 2021: 3690-3694 - [c203]Rong Wang, Jitao Lu, Yihang Lu, Feiping Nie, Xuelong Li:
Discrete Multiple Kernel k-means. IJCAI 2021: 3111-3117 - [c202]Danyang Wu, Jin Xu, Xia Dong, Meng Liao, Rong Wang, Feiping Nie, Xuelong Li:
GSPL: A Succinct Kernel Model for Group-Sparse Projections Learning of Multiview Data. IJCAI 2021: 3185-3191 - [c201]Xuesong Wang, Lina Yao, Xianzhi Wang, Feiping Nie, Boualem Benatallah:
NP-PROV: Neural Processes with Position-Relevant-Only Variances. WISE (1) 2021: 129-142 - [i37]Rong Wang, Wei Feng, Qianrong Zhang, Feiping Nie, Zhen Wang, Xuelong Li:
Ensemble and Random Collaborative Representation-Based Anomaly Detector for Hyperspectral Imagery. CoRR abs/2101.01976 (2021) - [i36]Wei Chang, Feiping Nie, Rong Wang, Xuelong Li:
New Tight Relaxations of Rank Minimization for Multi-Task Learning. CoRR abs/2112.04734 (2021) - 2020
- [j217]Libo Yang, Xuemei Liu, Feiping Nie, Yang Liu:
Robust and Efficient Linear Discriminant Analysis With L2, 1-Norm for Feature Selection. IEEE Access 8: 44100-44110 (2020) - [j216]Hui Yang, Han Peng, Jianyong Zhu, Feiping Nie:
Co-Clustering Ensemble Based on Bilateral K-Means Algorithm. IEEE Access 8: 51285-51294 (2020) - [j215]Tong Wu, Yanni Xiao, Muhan Guo, Feiping Nie:
A General Framework for Dimensionality Reduction of K-Means Clustering. J. Classif. 37(3): 616-631 (2020) - [j214]Chen Zhao, Wu Gao, Feiping Nie, Fei Wang, Huiyang Zhou:
Fair and cache blocking aware warp scheduling for concurrent kernel execution on GPU. Future Gener. Comput. Syst. 112: 1093-1105 (2020) - [j213]De-Yan Xie, Feiping Nie, Quanxue Gao, Song Xiao:
Fast algorithm for large-scale subspace clustering by LRR. IET Image Process. 14(8): 1475-1480 (2020) - [j212]Xiaojun Chen, Weijun Hong, Feiping Nie, Joshua Zhexue Huang, Li Shen:
Enhanced Balanced Min Cut. Int. J. Comput. Vis. 128(7): 1982-1995 (2020) - [j211]Fei Wang, Quan Wang, Feiping Nie, Weizhong Yu, Rong Wang, Zhongheng Li:
A forest of trees with principal direction specified oblique split on random subspace. Neurocomputing 379: 413-425 (2020) - [j210]Haifeng Zhao, Bowen Zhang, Zheng Wang, Feiping Nie:
Multiclass discriminant analysis via adaptive weighted scheme. Neurocomputing 381: 1-9 (2020) - [j209]Zhanxuan Hu, Feiping Nie, Wei Chang, Shuzheng Hao, Rong Wang, Xuelong Li:
Multi-view spectral clustering via sparse graph learning. Neurocomputing 384: 1-10 (2020) - [j208]Yijun Liu, Yongda Cai, Xiaojun Yang, Feiping Nie, Wujian Ye:
Fast adaptive neighbors clustering via embedded clustering. Neurocomputing 399: 331-341 (2020) - [j207]Shaojun Shi, Feiping Nie, Rong Wang, Xuelong Li:
Auto-weighted multi-view clustering via spectral embedding. Neurocomputing 399: 369-379 (2020) - [j206]Feiping Nie, Wei Zhu, Xuelong Li:
Decision Tree SVM: An extension of linear SVM for non-linear classification. Neurocomputing 401: 153-159 (2020) - [j205]Zhanxuan Hu, Feiping Nie, Rong Wang, Xuelong Li:
Multi-view spectral clustering via integrating nonnegative embedding and spectral embedding. Inf. Fusion 55: 251-259 (2020) - [j204]Lodewijk Brand, Xue Yang, Kai Liu, Saad Elbeleidy, Hua Wang, Hao Zhang, Feiping Nie:
Learning Robust Multilabel Sample Specific Distances for Identifying HIV-1 Drug Resistance. J. Comput. Biol. 27(4): 655-672 (2020) - [j203]Muhammad Adnan Ashraf, Rao Muhammad Adeel Nawab, Feiping Nie:
A study of deep learning methods for same-genre and cross-genre author profiling. J. Intell. Fuzzy Syst. 39(2): 2353-2363 (2020) - [j202]Muhammad Adnan Ashraf, Rao Muhammad Adeel Nawab, Feiping Nie:
Author profiling on bi-lingual tweets. J. Intell. Fuzzy Syst. 39(2): 2379-2389 (2020) - [j201]De-Yan Xie, Feiping Nie, Quanxue Gao:
On the optimal solution to maximum margin projection pursuit. Multim. Tools Appl. 79(47): 35441-35461 (2020) - [j200]Qi Wang, Mulin Chen, Feiping Nie, Xuelong Li:
Detecting Coherent Groups in Crowd Scenes by Multiview Clustering. IEEE Trans. Pattern Anal. Mach. Intell. 42(1): 46-58 (2020) - [j199]Feiping Nie, Shaojun Shi, Xuelong Li:
Auto-weighted multi-view co-clustering via fast matrix factorization. Pattern Recognit. 102: 107207 (2020) - [j198]Fei Wang, Quan Wang, Feiping Nie, Zhongheng Li, Weizhong Yu, Fuji Ren:
A linear multivariate binary decision tree classifier based on K-means splitting. Pattern Recognit. 107: 107521 (2020) - [j197]Xiaojun Yang, Weizhong Yu, Rong Wang, Guohao Zhang, Feiping Nie:
Fast spectral clustering learning with hierarchical bipartite graph for large-scale data. Pattern Recognit. Lett. 130: 345-352 (2020) - [j196]Rong Wang, Haojie Hu, Fang He, Feiping Nie, Shubin Cai, Zhong Ming:
Self-weighted collaborative representation for hyperspectral anomaly detection. Signal Process. 177: 107718 (2020) - [j195]Zheng Wang, Feiping Nie, Canyu Zhang, Rong Wang, Xuelong Li:
Capped ℓp-Norm LDA for Outliers Robust Dimension Reduction. IEEE Signal Process. Lett. 27: 1315-1319 (2020) - [j194]Danyang Wu, Han Zhang, Feiping Nie, Rong Wang, Chao Yang, Xiaoxue Jia, Xuelong Li:
Double-Attentive Principle Component Analysis. IEEE Signal Process. Lett. 27: 1814-1818 (2020) - [j193]Chen Zhao, Wu Gao, Feiping Nie:
A Memory-Efficient Hardware Architecture for Connected Component Labeling in Embedded System. IEEE Trans. Circuits Syst. Video Technol. 30(9): 3238-3252 (2020) - [j192]Lei Zhang, Ji Liu, Yang Yang, Fuxiang Huang, Feiping Nie, David Zhang:
Optimal Projection Guided Transfer Hashing for Image Retrieval. IEEE Trans. Circuits Syst. Video Technol. 30(10): 3788-3802 (2020) - [j191]Yanwei Pang, Jin Xie, Feiping Nie, Xuelong Li:
Spectral Clustering by Joint Spectral Embedding and Spectral Rotation. IEEE Trans. Cybern. 50(1): 247-258 (2020) - [j190]Feiping Nie, Zheng Wang, Rong Wang, Xuelong Li:
Submanifold-Preserving Discriminant Analysis With an Auto-Optimized Graph. IEEE Trans. Cybern. 50(8): 3682-3695 (2020) - [j189]Rui Zhang, Xuelong Li, Hongyuan Zhang, Feiping Nie:
Deep Fuzzy K-Means With Adaptive Loss and Entropy Regularization. IEEE Trans. Fuzzy Syst. 28(11): 2814-2824 (2020) - [j188]Rong Wang, Feiping Nie, Zhen Wang, Fang He, Xuelong Li:
Multiple Features and Isolation Forest-Based Fast Anomaly Detector for Hyperspectral Imagery. IEEE Trans. Geosci. Remote. Sens. 58(9): 6664-6676 (2020) - [j187]Xuelong Li, Han Zhang, Rui Zhang, Feiping Nie:
Discriminative and Uncorrelated Feature Selection With Constrained Spectral Analysis in Unsupervised Learning. IEEE Trans. Image Process. 29: 2139-2149 (2020) - [j186]Feiping Nie, Zheng Wang, Rong Wang, Zhen Wang, Xuelong Li:
Adaptive Local Linear Discriminant Analysis. ACM Trans. Knowl. Discov. Data 14(1): 9:1-9:19 (2020) - [j185]Xiaojun Chen, Guowen Yuan, Feiping Nie, Zhong Ming:
Semi-Supervised Feature Selection via Sparse Rescaled Linear Square Regression. IEEE Trans. Knowl. Data Eng. 32(1): 165-176 (2020) - [j184]Feiping Nie, Shaojun Shi, Xuelong Li:
Semi-Supervised Learning with Auto-Weighting Feature and Adaptive Graph. IEEE Trans. Knowl. Data Eng. 32(6): 1167-1178 (2020) - [j183]Jinglin Xu, Junwei Han, Feiping Nie, Xuelong Li:
Multi-View Scaling Support Vector Machines for Classification and Feature Selection. IEEE Trans. Knowl. Data Eng. 32(7): 1419-1430 (2020) - [j182]Rong Wang, Feiping Nie, Zhen Wang, Haojie Hu, Xuelong Li:
Parameter-Free Weighted Multi-View Projected Clustering with Structured Graph Learning. IEEE Trans. Knowl. Data Eng. 32(10): 2014-2025 (2020) - [j181]Feiping Nie, Lai Tian, Rong Wang, Xuelong Li:
Multiview Semi-Supervised Learning Model for Image Classification. IEEE Trans. Knowl. Data Eng. 32(12): 2389-2400 (2020) - [j180]Cheng Deng, Xu Yang, Feiping Nie, Dapeng Tao:
Saliency Detection via a Multiple Self-Weighted Graph-Based Manifold Ranking. IEEE Trans. Multim. 22(4): 885-896 (2020) - [j179]Yuebin Wang, Liqiang Zhang, Feiping Nie, Xingang Li, Zhijun Chen, Faqiang Wang:
WeGAN: Deep Image Hashing With Weighted Generative Adversarial Networks. IEEE Trans. Multim. 22(6): 1458-1469 (2020) - [j178]Xiaowei Zhao, Jun Guo, Feiping Nie, Ling Chen, Zhihui Li, Huaxiang Zhang:
Joint Principal Component and Discriminant Analysis for Dimensionality Reduction. IEEE Trans. Neural Networks Learn. Syst. 31(2): 433-444 (2020) - [j177]Fang He, Feiping Nie, Rong Wang, Xuelong Li, Weimin Jia:
Fast Semisupervised Learning With Bipartite Graph for Large-Scale Data. IEEE Trans. Neural Networks Learn. Syst. 31(2): 626-638 (2020) - [j176]Xiaojun Chen, Renjie Chen, Qingyao Wu, Yixiang Fang, Feiping Nie, Joshua Zhexue Huang:
LABIN: Balanced Min Cut for Large-Scale Data. IEEE Trans. Neural Networks Learn. Syst. 31(3): 725-736 (2020) - [j175]Runwu Zhou, Xiaojun Chang, Lei Shi, Yi-Dong Shen, Yi Yang, Feiping Nie:
Person Reidentification via Multi-Feature Fusion With Adaptive Graph Learning. IEEE Trans. Neural Networks Learn. Syst. 31(5): 1592-1601 (2020) - [j174]Kaixuan Chen, Lina Yao, Dalin Zhang, Xianzhi Wang, Xiaojun Chang, Feiping Nie:
A Semisupervised Recurrent Convolutional Attention Model for Human Activity Recognition. IEEE Trans. Neural Networks Learn. Syst. 31(5): 1747-1756 (2020) - [j173]Shuangyan Yi, Zhenyu He, Xiao-Yuan Jing, Yi Li, Yiu-Ming Cheung, Feiping Nie:
Adaptive Weighted Sparse Principal Component Analysis for Robust Unsupervised Feature Selection. IEEE Trans. Neural Networks Learn. Syst. 31(6): 2153-2163 (2020) - [j172]Yun Liu, Rui Zhang, Feiping Nie, Xuelong Li, Chris Ding:
Supervised Dimensionality Reduction Methods via Recursive Regression. IEEE Trans. Neural Networks Learn. Syst. 31(9): 3269-3279 (2020) - [j171]Feiping Nie, Danyang Wu, Rong Wang, Xuelong Li:
Self-Weighted Clustering With Adaptive Neighbors. IEEE Trans. Neural Networks Learn. Syst. 31(9): 3428-3441 (2020) - [j170]Rui Zhang, Han Zhang, Xuelong Li, Feiping Nie:
Adaptive Robust Low-Rank 2-D Reconstruction With Steerable Sparsity. IEEE Trans. Neural Networks Learn. Syst. 31(9): 3754-3759 (2020) - [j169]Pengzhen Ren, Yun Xiao, Xiaojun Chang, Mahesh Prakash, Feiping Nie, Xin Wang, Xiaojiang Chen:
Structured Optimal Graph-Based Clustering With Flexible Embedding. IEEE Trans. Neural Networks Learn. Syst. 31(10): 3801-3813 (2020) - [c200]Xuanrong Pang, Xiaojun Chen, Shu Yang, Feiping Nie:
Unsupervised Deep Hashing with Structured Similarity Learning. APWeb/WAIM (2) 2020: 500-514 - [c199]Lyujian Lu, Hua Wang, Saad Elbeleidy, Feiping Nie:
Predicting Cognitive Declines Using Longitudinally Enriched Representations for Imaging Biomarkers. CVPR 2020: 4826-4835 - [c198]Jikui Wang, Quanfu Shi, Zhengguo Yang, Feiping Nie:
Clustering by Unified Principal Component Analysis and Fuzzy C-Means with Sparsity Constraint. ICA3PP (2) 2020: 337-351 - [c197]Feiping Nie, Shenfei Pei, Rong Wang, Xuelong Li:
Fast Clustering With Co-Clustering Via Discrete Non-Negative Matrix Factorization for Image Identification. ICASSP 2020: 2073-2077 - [c196]Cheng-Long Wang, Feiping Nie, Rong Wang, Xuelong Li:
Revisiting Fast Spectral Clustering with Anchor Graph. ICASSP 2020: 3902-3906 - [c195]Danyang Wu, Feiping Nie, Rong Wang, Xuelong Li:
Multi-View Clustering Via Mixed Embedding Approximation. ICASSP 2020: 3977-3981 - [c194]Yong Peng, Rixin Tang, Wanzeng Kong, Feiping Nie:
A Factorized Extreme Learning Machine and Its Applications in EEG-Based Emotion Recognition. ICONIP (5) 2020: 11-20 - [c193]Zheng Wang, Feiping Nie, Lai Tian, Rong Wang, Xuelong Li:
Discriminative Feature Selection via A Structured Sparse Subspace Learning Module. IJCAI 2020: 3009-3015 - [c192]Feiping Nie, Han Zhang, Rong Wang, Xuelong Li:
Semi-supervised Clustering via Pairwise Constrained Optimal Graph. IJCAI 2020: 3160-3166 - [c191]Shenfei Pei, Feiping Nie, Rong Wang, Xuelong Li:
Efficient Clustering Based On A Unified View Of $K$-means And Ratio-cut. NeurIPS 2020 - [c190]Lai Tian, Feiping Nie, Rong Wang, Xuelong Li:
Learning Feature Sparse Principal Subspace. NeurIPS 2020 - [i35]Di Hu, Zheng Wang, Haoyi Xiong, Dong Wang, Feiping Nie, Dejing Dou:
Curriculum Audiovisual Learning. CoRR abs/2001.09414 (2020) - [i34]Zhe Liu, Yun Li, Lina Yao, Xianzhi Wang, Feiping Nie:
Agglomerative Neural Networks for Multi-view Clustering. CoRR abs/2005.05556 (2020) - [i33]Xuesong Wang, Lina Yao, Xianzhi Wang, Feiping Nie:
NP-PROV: Neural Processes with Position-Relevant-Only Variances. CoRR abs/2007.00767 (2020) - [i32]Caixia Yan, Xiaojun Chang, Minnan Luo, Qinghua Zheng, Xiaoqin Zhang, Zhihui Li, Feiping Nie:
Self-Weighted Robust LDA for Multiclass Classification with Edge Classes. CoRR abs/2009.12362 (2020) - [i31]Zhengxin Li, Feiping Nie, Jintang Bian, Xuelong Li:
Sparse PCA via $l_{2, p}$-Norm Regularization for Unsupervised Feature Selection. CoRR abs/2012.14595 (2020)
2010 – 2019
- 2019
- [j168]Fei Wang, Zhongheng Li, Fang He, Rong Wang, Weizhong Yu, Feiping Nie:
Feature Learning Viewpoint of Adaboost and a New Algorithm. IEEE Access 7: 149890-149899 (2019) - [j167]Zhengxin Li, Jiansheng Guo, Hailin Li, Tao Wu, Sheng Mao, Feiping Nie:
Speed Up Similarity Search of Time Series Under Dynamic Time Warping. IEEE Access 7: 163644-163653 (2019) - [j166]Pu Zhang, Siyang Deng, Feiping Nie, Yang Liu, Xiangdong Zhang, Quanxue Gao:
Nuclear-norm based 2DLDA with application to face recognition. Neurocomputing 339: 94-104 (2019) - [j165]Tong Wu, Yicang Zhou, Yanni Xiao, Deanna Needell, Feiping Nie:
Modified fuzzy clustering with segregated cluster centroids. Neurocomputing 361: 10-18 (2019) - [j164]Han Zhang, Rui Zhang, Feiping Nie, Xuelong Li:
An efficient framework for unsupervised feature selection. Neurocomputing 366: 194-207 (2019) - [j163]Rui Zhang, Feiping Nie, Xuelong Li, Xian Wei:
Feature selection with multi-view data: A survey. Inf. Fusion 50: 158-167 (2019) - [j162]Zhengxin Li, Fengming Zhang, Feiping Nie, Hailin Li, Jian Wang:
Speed up dynamic time warpingof multivariate time series. J. Intell. Fuzzy Syst. 36(3): 2593-2603 (2019) - [j161]Haojie Hu, Rong Wang, Xiaojun Yang, Feiping Nie:
Scalable and Flexible Unsupervised Feature Selection. Neural Comput. 31(3) (2019) - [j160]Yang Liu, Feiping Nie, Quanxue Gao, Xinbo Gao, Jungong Han, Ling Shao:
Flexible unsupervised feature extraction for image classification. Neural Networks 115: 65-71 (2019) - [j159]Muli Yang, Cheng Deng, Feiping Nie:
Adaptive-weighting discriminative regression for multi-view classification. Pattern Recognit. 88: 236-245 (2019) - [j158]Xinyi Xu, Yanhua Yang, Cheng Deng, Feiping Nie:
Adaptive graph weighting for multi-view dimensionality reduction. Signal Process. 165: 186-196 (2019) - [j157]Suo Qiu, Feiping Nie, Xiangmin Xu, Chunmei Qing, Dong Xu:
Accelerating Flexible Manifold Embedding for Scalable Semi-Supervised Learning. IEEE Trans. Circuits Syst. Video Technol. 29(9): 2786-2795 (2019) - [j156]Lingling Zhang, Minnan Luo, Zhihui Li, Feiping Nie, Huaxiang Zhang, Jun Liu, Qinghua Zheng:
Large-Scale Robust Semisupervised Classification. IEEE Trans. Cybern. 49(3): 907-917 (2019) - [j155]Tingjin Luo, Chenping Hou, Feiping Nie, Dongyun Yi:
Dimension Reduction for Non-Gaussian Data by Adaptive Discriminative Analysis. IEEE Trans. Cybern. 49(3): 933-946 (2019) - [j154]Rong Wang, Feiping Nie, Zhen Wang, Fang He, Xuelong Li:
Scalable Graph-Based Clustering With Nonnegative Relaxation for Large Hyperspectral Image. IEEE Trans. Geosci. Remote. Sens. 57(10): 7352-7364 (2019) - [j153]Di Hu, Feiping Nie, Xuelong Li:
Discrete Spectral Hashing for Efficient Similarity Retrieval. IEEE Trans. Image Process. 28(3): 1080-1091 (2019) - [j152]Kun Zhan, Feiping Nie, Jing Wang, Yi Yang:
Multiview Consensus Graph Clustering. IEEE Trans. Image Process. 28(3): 1261-1270 (2019) - [j151]Rui Zhang, Feiping Nie, Muhan Guo, Xian Wei, Xuelong Li:
Joint Learning of Fuzzy k-Means and Nonnegative Spectral Clustering With Side Information. IEEE Trans. Image Process. 28(5): 2152-2162 (2019) - [j150]Feiping Nie, Zhanxuan Hu, Xuelong Li:
Matrix Completion Based on Non-Convex Low-Rank Approximation. IEEE Trans. Image Process. 28(5): 2378-2388 (2019) - [j149]Feiping Nie, Sheng Yang, Rui Zhang, Xuelong Li:
A General Framework for Auto-Weighted Feature Selection via Global Redundancy Minimization. IEEE Trans. Image Process. 28(5): 2428-2438 (2019) - [j148]Feiping Nie, Han Zhang, Rui Zhang, Xuelong Li:
Robust Multiple Rank-k Bilinear Projections for Unsupervised Learning. IEEE Trans. Image Process. 28(5): 2574-2583 (2019) - [j147]Minnan Luo, Caixia Yan, Qinghua Zheng, Xiaojun Chang, Ling Chen, Feiping Nie:
Discrete Multi-Graph Clustering. IEEE Trans. Image Process. 28(9): 4701-4712 (2019) - [j146]Haifeng Zhao, Zheng Wang, Feiping Nie:
A New Formulation of Linear Discriminant Analysis for Robust Dimensionality Reduction. IEEE Trans. Knowl. Data Eng. 31(4): 629-640 (2019) - [j145]Tianji Pang, Feiping Nie, Junwei Han, Xuelong Li:
Efficient Feature Selection via $\ell _{2, 0}$ℓ2, 0-norm Constrained Sparse Regression. IEEE Trans. Knowl. Data Eng. 31(5): 880-893 (2019) - [j144]Shuai Zheng, Chris Ding, Feiping Nie, Heng Huang:
Harmonic Mean Linear Discriminant Analysis. IEEE Trans. Knowl. Data Eng. 31(8): 1520-1531 (2019) - [j143]Kun Zhan, Chaoxi Niu, Changlu Chen, Feiping Nie, Changqing Zhang, Yi Yang:
Graph Structure Fusion for Multiview Clustering. IEEE Trans. Knowl. Data Eng. 31(10): 1984-1993 (2019) - [j142]Di Hu, Feiping Nie, Xuelong Li:
Deep Binary Reconstruction for Cross-Modal Hashing. IEEE Trans. Multim. 21(4): 973-985 (2019) - [j141]Xingzhong Du, Feiping Nie, Weiqing Wang, Yi Yang, Xiaofang Zhou:
Exploiting Combination Effect for Unsupervised Feature Selection by ℓ2, 0 Norm. IEEE Trans. Neural Networks Learn. Syst. 30(1): 201-214 (2019) - [j140]Rui Zhang, Feiping Nie, Xuelong Li:
Semisupervised Learning With Parameter-Free Similarity of Label and Side Information. IEEE Trans. Neural Networks Learn. Syst. 30(2): 405-414 (2019) - [j139]Qi Wang, Zequn Qin, Feiping Nie, Xuelong Li:
Spectral Embedded Adaptive Neighbors Clustering. IEEE Trans. Neural Networks Learn. Syst. 30(4): 1265-1271 (2019) - [j138]Qi Wang, Jia Wan, Feiping Nie, Bo Liu, Chenggang Yan, Xuelong Li:
Hierarchical Feature Selection for Random Projection. IEEE Trans. Neural Networks Learn. Syst. 30(5): 1581-1586 (2019) - [j137]Xuelong Li, Han Zhang, Rui Zhang, Yun Liu, Feiping Nie:
Generalized Uncorrelated Regression with Adaptive Graph for Unsupervised Feature Selection. IEEE Trans. Neural Networks Learn. Syst. 30(5): 1587-1595 (2019) - [j136]Yanwei Pang, Bo Zhou, Feiping Nie:
Simultaneously Learning Neighborship and Projection Matrix for Supervised Dimensionality Reduction. IEEE Trans. Neural Networks Learn. Syst. 30(9): 2779-2793 (2019) - [j135]Rui Zhang, Feiping Nie, Yunhai Wang, Xuelong Li:
Unsupervised Feature Selection via Adaptive Multimeasure Fusion. IEEE Trans. Neural Networks Learn. Syst. 30(9): 2886-2892 (2019) - [j134]Junwei Han, Hanyang Liu, Feiping Nie:
A Local and Global Discriminative Framework and Optimization for Balanced Clustering. IEEE Trans. Neural Networks Learn. Syst. 30(10): 3059-3071 (2019) - [c189]Di Ming, Chris Ding, Feiping Nie:
A Probabilistic Derivation of LASSO and L12-Norm Feature Selections. AAAI 2019: 4586-4593 - [c188]Weichan Zhong, Xiaojun Chen, Guowen Yuan, Yiqin Li, Feiping Nie:
Semi-Supervised Feature Selection with Adaptive Discriminant Analysis. AAAI 2019: 10083-10084 - [c187]Lai Tian, Feiping Nie, Xuelong Li:
A Unified Weight Learning Paradigm for Multi-view Learning. AISTATS 2019: 2790-2800 - [c186]Di Hu, Dong Wang, Xuelong Li, Feiping Nie, Qi Wang:
Listen to the Image. CVPR 2019: 7972-7981 - [c185]Di Hu, Feiping Nie, Xuelong Li:
Deep Multimodal Clustering for Unsupervised Audiovisual Learning. CVPR 2019: 9248-9257 - [c184]Sheng Yang, Rui Zhang, Feiping Nie, Xuelong Li:
Unsupervised Feature Selection Based on Reconstruction Error Minimization. ICASSP 2019: 2107-2111 - [c183]Yong Peng, Yanfang Long, Feiwei Qin, Wanzeng Kong, Feiping Nie, Andrzej Cichocki:
Flexible Non-negative Matrix Factorization with Adaptively Learned Graph Regularization. ICASSP 2019: 3107-3111 - [c182]Yong Peng, Rixin Tang, Wanzeng Kong, Jianhai Zhang, Feiping Nie, Andrzej Cichocki:
Joint Structured Graph Learning and Clustering Based on Concept Factorization. ICASSP 2019: 3162-3166 - [c181]Yong Peng, Leijie Zhang, Wanzeng Kong, Feiping Nie, Andrzej Cichocki:
Joint Structured Graph Learning and Unsupervised Feature Selection. ICASSP 2019: 3572-3576 - [c180]Wei Chang, Feiping Nie, Rong Wang, Xuelong Li:
Robust Subspace Clustering by Learning an Optimal Structured Bipartite Graph via Low-rank Representation. ICASSP 2019: 3692-3696 - [c179]Di Hu, Chengze Wang, Feiping Nie, Xuelong Li:
Dense Multimodal Fusion for Hierarchically Joint Representation. ICASSP 2019: 3941-3945 - [c178]Shuangli Liao, Quanxue Gao, Feiping Nie, Yang Liu, Xiangdong Zhang:
Worst-Case Discriminative Feature Selection. IJCAI 2019: 2973-2979 - [c177]Kai Liu, Lodewijk Brand, Hua Wang, Feiping Nie:
Learning Robust Distance Metric with Side Information via Ratio Minimization of Orthogonally Constrained L21-Norm Distances. IJCAI 2019: 3008-3014 - [c176]Haoxuan Yang, Kai Liu, Hua Wang, Feiping Nie:
Learning Strictly Orthogonal p-Order Nonnegative Laplacian Embedding via Smoothed Iterative Reweighted Method. IJCAI 2019: 4040-4046 - [c175]Feiping Nie, Cheng-Long Wang, Xuelong Li:
K-Multiple-Means: A Multiple-Means Clustering Method with Specified K Clusters. KDD 2019: 959-967 - [c174]Defu Yang, Chenggang Yan, Feiping Nie, Xiaofeng Zhu, Md Asadullah Turja, Leo Charles Peek Zsembik, Martin Styner, Guorong Wu:
Joint Identification of Network Hub Nodes by Multivariate Graph Inference. MICCAI (3) 2019: 590-598 - [i30]Fei Wang, Zhongheng Li, Fang He, Rong Wang, Weizhong Yu, Feiping Nie:
Feature Learning Viewpoint of AdaBoost and a New Algorithm. CoRR abs/1904.03953 (2019) - [i29]Di Hu, Dong Wang, Xuelong Li, Feiping Nie, Qi Wang:
Listen to the Image. CoRR abs/1904.09115 (2019) - [i28]Lai Tian, Feiping Nie, Xuelong Li:
Learning Feature Sparse Principal Components. CoRR abs/1904.10155 (2019) - [i27]Feiping Nie, Jing Li, Xuelong Li:
Intrinsic Weight Learning Approach for Multi-view Clustering. CoRR abs/1906.08905 (2019) - [i26]Feiping Nie, Hua Wang, Zheng Wang, Heng Huang:
Robust Linear Discriminant Analysis Using Ratio Minimization of L1, 2-Norms. CoRR abs/1907.00211 (2019) - [i25]Feiping Nie, Zhanxuan Hu, Xiaoqian Wang, Rong Wang, Xuelong Li, Heng Huang:
An Iteratively Re-weighted Method for Problems with Sparsity-Inducing Norms. CoRR abs/1907.01121 (2019) - [i24]Jinglin Xu, Junwei Han, Feiping Nie, Xuelong Li:
Robust and Efficient Fuzzy C-Means Clustering Constrained on Flexible Sparsity. CoRR abs/1908.06699 (2019) - [i23]Xia Wu, Xueyuan Xu, Jianhong Liu, Hailing Wang, Bin Hu, Feiping Nie:
Supervised feature selection with orthogonal regression and feature weighting. CoRR abs/1910.03787 (2019) - 2018
- [j133]Feiping Nie, Zhanxuan Hu, Xuelong Li:
An investigation for loss functions widely used in machine learning. Commun. Inf. Syst. 18(1): 37-52 (2018) - [j132]Yong Peng, Wanzeng Kong, Feiwei Qin, Feiping Nie:
Manifold Adaptive Kernelized Low-Rank Representation for Semisupervised Image Classification. Complex. 2018: 2857594:1-2857594:11 (2018) - [j131]Yong Peng, Wanzeng Kong, Feiwei Qin, Feiping Nie:
Corrigendum to "Manifold Adaptive Kernelized Low-Rank Representation for Semisupervised Image Classification". Complex. 2018: 6975152:1 (2018) - [j130]Rui Zhang, Feiping Nie, Xuelong Li:
Feature selection under regularized orthogonal least square regression with optimal scaling. Neurocomputing 273: 547-553 (2018) - [j129]Yang Liu, Feiping Nie, Quanxue Gao:
Nuclear-norm based semi-supervised multiple labels learning. Neurocomputing 275: 940-947 (2018) - [j128]Tong Wu, Yicang Zhou, Rui Zhang, Yanni Xiao, Feiping Nie:
Self-weighted discriminative feature selection via adaptive redundancy minimization. Neurocomputing 275: 2824-2830 (2018) - [j127]Xiaoshuang Shi, Feiping Nie, Zhihui Lai, Zhenhua Guo:
Robust principal component analysis via optimal mean by joint ℓ2, 1 and Schatten p-norms minimization. Neurocomputing 283: 205-213 (2018) - [j126]Gongmin Lan, Chenping Hou, Feiping Nie, Tingjin Luo, Dongyun Yi:
Robust feature selection via simultaneous sapped norm and sparse regularizer minimization. Neurocomputing 283: 228-240 (2018) - [j125]Fei Wang, Quan Wang, Feiping Nie, Weizhong Yu, Rong Wang:
Efficient tree classifiers for large scale datasets. Neurocomputing 284: 70-79 (2018) - [j124]Zhe Liu, Zhanxuan Hu, Feiping Nie:
Matrix completion and vector completion via robust subspace learning. Neurocomputing 306: 171-181 (2018) - [j123]Yue Song, Yang Liu, Quanxue Gao, Xinbo Gao, Feiping Nie, Rongmei Cui:
Euler Label Consistent K-SVD for image classification and action recognition. Neurocomputing 310: 277-286 (2018) - [j122]Haifeng Zhao, Zheng Wang, Feiping Nie:
Adaptive Neighborhood MinMax Projections. Neurocomputing 313: 155-166 (2018) - [j121]Weizhong Yu, Rong Wang, Feiping Nie, Fei Wang:
Multi-view embedded clustering with unsupervised trace ratio LDA. Neurocomputing 315: 169-176 (2018) - [j120]Weizhong Yu, Rong Wang, Feiping Nie, Fei Wang, Qiang Yu, Xiaojun Yang:
An improved locality preserving projection with ℓ1-norm minimization for dimensionality reduction. Neurocomputing 316: 322-331 (2018) - [j119]Yang Zhao, Yuan Yuan, Feiping Nie, Qi Wang:
Spectral clustering based on iterative optimization for large-scale and high-dimensional data. Neurocomputing 318: 227-235 (2018) - [j118]Weizhong Yu, Feiping Nie, Fei Wang, Rong Wang, Xuelong Li:
Fast and Flexible Large Graph Embedding Based on Anchors. IEEE J. Sel. Top. Signal Process. 12(6): 1465-1475 (2018) - [j117]Haojie Hu, Rong Wang, Feiping Nie, Xiaojun Yang, Weizhong Yu:
Fast unsupervised feature selection with anchor graph and ℓ 2, 1-norm regularization. Multim. Tools Appl. 77(17): 22099-22113 (2018) - [j116]Yang Liu, Kaiwen Wen, Quanxue Gao, Xinbo Gao, Feiping Nie:
SVM based multi-label learning with missing labels for image annotation. Pattern Recognit. 78: 307-317 (2018) - [j115]Han Zhang, Feiping Nie, Rui Zhang, Xuelong Li:
Auto-weighted 2-dimensional maximum margin criterion. Pattern Recognit. 83: 220-229 (2018) - [j114]Quanxue Gao, Lan Ma, Yang Liu, Xinbo Gao, Feiping Nie:
Angle 2DPCA: A New Formulation for 2DPCA. IEEE Trans. Cybern. 48(5): 1672-1678 (2018) - [j113]Xiaowei Xue, Feiping Nie, Zhihui Li, Sen Wang, Xue Li, Min Yao:
A Multiview Learning Framework With a Linear Computational Cost. IEEE Trans. Cybern. 48(8): 2416-2425 (2018) - [j112]Yuebin Wang, Liqiang Zhang, Xiaohua Tong, Feiping Nie, Haiyang Huang, Jie Mei:
LRAGE: Learning Latent Relationships With Adaptive Graph Embedding for Aerial Scene Classification. IEEE Trans. Geosci. Remote. Sens. 56(2): 621-634 (2018) - [j111]Qianqian Wang, Quanxue Gao, Xinbo Gao, Feiping Nie:
ℓ2, p -Norm Based PCA for Image Recognition. IEEE Trans. Image Process. 27(3): 1336-1346 (2018) - [j110]Feiping Nie, Guohao Cai, Jing Li, Xuelong Li:
Auto-Weighted Multi-View Learning for Image Clustering and Semi-Supervised Classification. IEEE Trans. Image Process. 27(3): 1501-1511 (2018) - [j109]Junwei Han, Rong Quan, Dingwen Zhang, Feiping Nie:
Robust Object Co-Segmentation Using Background Prior. IEEE Trans. Image Process. 27(4): 1639-1651 (2018) - [j108]Wei Wang, Yan Yan, Feiping Nie, Shuicheng Yan, Nicu Sebe:
Flexible Manifold Learning With Optimal Graph for Image and Video Representation. IEEE Trans. Image Process. 27(6): 2664-2675 (2018) - [j107]Liangchen Liu, Feiping Nie, Arnold Wiliem, Zhihui Li, Teng Zhang, Brian C. Lovell:
Multi-Modal Joint Clustering With Application for Unsupervised Attribute Discovery. IEEE Trans. Image Process. 27(9): 4345-4356 (2018) - [j106]Shuangli Liao, Quanxue Gao, Zhaohua Yang, Fang Chen, Feiping Nie, Jungong Han:
Discriminant Analysis via Joint Euler Transform and ℓ2, 1-Norm. IEEE Trans. Image Process. 27(11): 5668-5682 (2018) - [j105]Xiaojun Chen, Yixiang Fang, Min Yang, Feiping Nie, Zhou Zhao, Joshua Zhexue Huang:
PurTreeClust: A Clustering Algorithm for Customer Segmentation from Massive Customer Transaction Data. IEEE Trans. Knowl. Data Eng. 30(3): 559-572 (2018) - [j104]Tingjin Luo, Chenping Hou, Feiping Nie, Hong Tao, Dongyun Yi:
Semi-Supervised Feature Selection via Insensitive Sparse Regression with Application to Video Semantic Recognition. IEEE Trans. Knowl. Data Eng. 30(10): 1943-1956 (2018) - [j103]Rong Quan, Junwei Han, Dingwen Zhang, Feiping Nie, Xueming Qian, Xuelong Li:
Unsupervised Salient Object Detection via Inferring From Imperfect Saliency Models. IEEE Trans. Multim. 20(5): 1101-1112 (2018) - [j102]Minnan Luo, Feiping Nie, Xiaojun Chang, Yi Yang, Alexander G. Hauptmann, Qinghua Zheng:
Adaptive Unsupervised Feature Selection With Structure Regularization. IEEE Trans. Neural Networks Learn. Syst. 29(4): 944-956 (2018) - [j101]Kun Song, Feiping Nie, Junwei Han, Xuelong Li:
Rank-k 2-D Multinomial Logistic Regression for Matrix Data Classification. IEEE Trans. Neural Networks Learn. Syst. 29(8): 3524-3537 (2018) - [j100]Rui Zhang, Feiping Nie, Xuelong Li:
Self-Weighted Supervised Discriminative Feature Selection. IEEE Trans. Neural Networks Learn. Syst. 29(8): 3913-3918 (2018) - [j99]Chao Yao, Junwei Han, Feiping Nie, Fu Xiao, Xuelong Li:
Local Regression and Global Information-Embedded Dimension Reduction. IEEE Trans. Neural Networks Learn. Syst. 29(10): 4882-4893 (2018) - [j98]Zhihui Li, Feiping Nie, Xiaojun Chang, Liqiang Nie, Huaxiang Zhang, Yi Yang:
Rank-Constrained Spectral Clustering With Flexible Embedding. IEEE Trans. Neural Networks Learn. Syst. 29(12): 6073-6082 (2018) - [j97]Zhihui Li, Feiping Nie, Xiaojun Chang, Yi Yang, Chengqi Zhang, Nicu Sebe:
Dynamic Affinity Graph Construction for Spectral Clustering Using Multiple Features. IEEE Trans. Neural Networks Learn. Syst. 29(12): 6323-6332 (2018) - [j96]Xiaojun Chen, Guowen Yuan, Wenting Wang, Feiping Nie, Xiaojun Chang, Joshua Zhexue Huang:
Local Adaptive Projection Framework for Feature Selection of Labeled and Unlabeled Data. IEEE Trans. Neural Networks Learn. Syst. 29(12): 6362-6373 (2018) - [c173]Zhihui Li, Feiping Nie, Xiaojun Chang, Zhigang Ma, Yi Yang:
Balanced Clustering via Exclusive Lasso: A Pragmatic Approach. AAAI 2018: 3596-3603 - [c172]Xu Yang, Cheng Deng, Xianglong Liu, Feiping Nie:
New l2, 1-Norm Relaxation of Multi-Way Graph Cut for Clustering. AAAI 2018: 4374-4381 - [c171]Zhihui Li, Lina Yao, Feiping Nie, Dingwen Zhang, Min Xu:
Multi-Rate Gated Recurrent Convolutional Networks for Video-Based Pedestrian Re-Identification. AAAI 2018: 7081-7088 - [c170]Guowen Yuan, Xiaojun Chen, Chen Wang, Feiping Nie, Liping Jing:
Discriminative Semi-Supervised Feature Selection via Rescaled Least Squares Regression-Supplement. AAAI 2018: 8177-8178 - [c169]Muhan Guo, Rui Zhang, Feiping Nie, Xuelong Li:
Embedding Fuzzy K-Means with Nonnegative Spectral Clustering via Incorporating Side Information. CIKM 2018: 1567-1570 - [c168]Kai Liu, Hua Wang, Feiping Nie, Hao Zhang:
Learning Multi-Instance Enriched Image Representations via Non-Greedy Ratio Maximization of the l1-Norm Distances. CVPR 2018: 7727-7735 - [c167]Yong Peng, Rixin Tang, Wanzeng Kong, Feiwei Qin, Feiping Nie:
Parallel Vector Field Regularized Non-Negative Matrix Factorization for Image Representation. ICASSP 2018: 2216-2220 - [c166]Jing Li, Feiping Nie, Xuelong Li:
Directly Solving the Original Ratiocut Problem for Effective Data Clustering. ICASSP 2018: 2306-2310 - [c165]Han Zhang, Rui Zhang, Feiping Nie, Xuelong Li:
A Generalized Uncorrelated Ridge Regression with Nonnegative Labels for Unsupervised Feature Selection. ICASSP 2018: 2781-2785 - [c164]Guohao Cai, Rui Zhang, Feiping Nie, Xuelong Li:
Feature Selection via Incorporating Stiefel Manifold in Relaxed K-Means. ICIP 2018: 1503-1507 - [c163]Muhan Guo, Sheng Yang, Feiping Nie, Xuelong Li:
Locality-Based Discriminant Feature Selection with Trace Ratio. ICIP 2018: 3373-3377 - [c162]Muhan Guo, Feiping Nie, Xuelong Li:
Self-Weighted Adaptive Locality Discriminant Analysis. ICIP 2018: 3378-3382 - [c161]Sheng Yang, Feiping Nie, Xuelong Li:
Unsupervised Feature Selection with Local Structure Learning. ICIP 2018: 3398-3402 - [c160]Zhanxuan Hu, Feiping Nie, Xuelong Li:
Robust Low Rank Approxiamtion via Inliers Selection. ICIP 2018: 3688-3692 - [c159]Xiaojun Chen, Weijun Hong, Feiping Nie, Dan He, Min Yang, Joshua Zhexue Huang:
Spectral Clustering of Large-scale Data by Directly Solving Normalized Cut. KDD 2018: 1206-1215 - [c158]Feiping Nie, Zhanxuan Hu, Xuelong Li:
Calibrated Multi-Task Learning. KDD 2018: 2012-2021 - [c157]Feiping Nie, Lai Tian, Xuelong Li:
Multiview Clustering via Adaptively Weighted Procrustes. KDD 2018: 2022-2030 - [i22]Muge Li, Liangyue Li, Feiping Nie:
Ranking with Adaptive Neighbors. CoRR abs/1803.05105 (2018) - [i21]Shuai Zheng, Chris H. Q. Ding, Feiping Nie:
Regularized Singular Value Decomposition and Application to Recommender System. CoRR abs/1804.05090 (2018) - [i20]Di Hu, Feiping Nie, Xuelong Li:
Deep Co-Clustering for Unsupervised Audiovisual Learning. CoRR abs/1807.03094 (2018) - [i19]Zhanxuan Hu, Feiping Nie, Lai Tian, Xuelong Li:
A Comprehensive Survey for Low Rank Regularization. CoRR abs/1808.04521 (2018) - [i18]Di Hu, Feiping Nie, Xuelong Li:
Deep LDA Hashing. CoRR abs/1810.03402 (2018) - [i17]Di Hu, Feiping Nie, Xuelong Li:
Dense Multimodal Fusion for Hierarchically Joint Representation. CoRR abs/1810.03414 (2018) - 2017
- [j95]Yunhai Wang, Jingting Li, Feiping Nie, Holger Theisel, Minglun Gong, Dirk J. Lehmann:
Linear Discriminative Star Coordinates for Exploring Class and Cluster Separation of High Dimensional Data. Comput. Graph. Forum 36(3): 401-410 (2017) - [j94]Feiping Nie, Rui Zhang, Xuelong Li:
A generalized power iteration method for solving quadratic problem on the Stiefel manifold. Sci. China Inf. Sci. 60(11): 112101:1-112101:10 (2017) - [j93]Xiaojun Chen, Si Peng, Joshua Zhexue Huang, Feiping Nie, Yong Ming:
Local PurTree Spectral Clustering for Massive Customer Transaction Data. IEEE Intell. Syst. 32(2): 37-44 (2017) - [j92]Mengfan Tang, Feiping Nie, Ramesh C. Jain:
A graph regularized dimension reduction method for out-of-sample data. Neurocomputing 225: 58-63 (2017) - [j91]Rui Zhang, Feiping Nie, Xuelong Li:
Self-weighted spectral clustering with parameter-free constraint. Neurocomputing 241: 164-170 (2017) - [j90]Mengfan Tang, Feiping Nie, Siripen Pongpaichet, Ramesh C. Jain:
Semi-supervised learning on large-scale geotagged photos for situation recognition. J. Vis. Commun. Image Represent. 48: 310-316 (2017) - [j89]Rong Wang, Feiping Nie, Weizhong Yu:
Fast Spectral Clustering With Anchor Graph for Large Hyperspectral Images. IEEE Geosci. Remote. Sens. Lett. 14(11): 2003-2007 (2017) - [j88]Zhengxia Wang, Xiaofeng Zhu, Ehsan Adeli, Yingying Zhu, Feiping Nie, Brent C. Munsell, Guorong Wu:
Multi-modal classification of neurodegenerative disease by progressive graph-based transductive learning. Medical Image Anal. 39: 218-230 (2017) - [j87]Minnan Luo, Feiping Nie, Xiaojun Chang, Yi Yang, Alexander G. Hauptmann, Qinghua Zheng:
Avoiding Optimal Mean ℓ2, 1-Norm Maximization-Based Robust PCA for Reconstruction. Neural Comput. 29(4): 1124-1150 (2017) - [j86]Xiaowei Zhao, Feiping Nie, Sen Wang, Jun Guo, Pengfei Xu, Xiaojiang Chen:
Unsupervised 2D Dimensionality Reduction with Adaptive Structure Learning. Neural Comput. 29(5): 1352-1374 (2017) - [j85]De Cheng, Feiping Nie, Jiande Sun, Yihong Gong:
A Weight-Adaptive Laplacian Embedding for Graph-Based Clustering. Neural Comput. 29(7): 1902-1918 (2017) - [j84]Yan-shuo Chang, Feiping Nie, Ming-Yu Wang:
Multiview Feature Analysis via Structured Sparsity and Shared Subspace Discovery. Neural Comput. 29(7): 1986-2003 (2017) - [j83]Yan-shuo Chang, Feiping Nie, Zhihui Li, Xiaojun Chang, Heng Huang:
Refined Spectral Clustering via Embedded Label Propagation. Neural Comput. 29(12) (2017) - [j82]Qianqian Wang, Quanxue Gao, Xinbo Gao, Feiping Nie:
Optimal mean two-dimensional principal component analysis with F-norm minimization. Pattern Recognit. 68: 286-294 (2017) - [j81]Yang Liu, Quanxue Gao, Shuo Miao, Xinbo Gao, Feiping Nie, Yunsong Li:
A Non-Greedy Algorithm for L1-Norm LDA. IEEE Trans. Image Process. 26(2): 684-695 (2017) - [j80]Jinglin Xu, Junwei Han, Feiping Nie, Xuelong Li:
Re-Weighted Discriminatively Embedded K-Means for Multi-View Clustering. IEEE Trans. Image Process. 26(6): 3016-3027 (2017) - [j79]Xiwen Yao, Junwei Han, Dingwen Zhang, Feiping Nie:
Revisiting Co-Saliency Detection: A Novel Approach Based on Two-Stage Multi-View Spectral Rotation Co-clustering. IEEE Trans. Image Process. 26(7): 3196-3209 (2017) - [j78]Chenping Hou, Yuanyuan Jiao, Feiping Nie, Tingjin Luo, Zhi-Hua Zhou:
2D Feature Selection by Sparse Matrix Regression. IEEE Trans. Image Process. 26(9): 4255-4268 (2017) - [j77]Hong Tao, Chenping Hou, Feiping Nie, Jubo Zhu, Dongyun Yi:
Scalable Multi-View Semi-Supervised Classification via Adaptive Regression. IEEE Trans. Image Process. 26(9): 4283-4296 (2017) - [j76]Rong Wang, Feiping Nie, Richang Hong, Xiaojun Chang, Xiaojun Yang, Weizhong Yu:
Fast and Orthogonal Locality Preserving Projections for Dimensionality Reduction. IEEE Trans. Image Process. 26(10): 5019-5030 (2017) - [j75]Feiping Nie, Jing Li, Xuelong Li:
Convex Multiview Semi-Supervised Classification. IEEE Trans. Image Process. 26(12): 5718-5729 (2017) - [j74]Chenping Hou, Feiping Nie, Hong Tao, Dongyun Yi:
Multi-View Unsupervised Feature Selection with Adaptive Similarity and View Weight. IEEE Trans. Knowl. Data Eng. 29(9): 1998-2011 (2017) - [j73]Zhihui Li, Feiping Nie, Xiaojun Chang, Yi Yang:
Beyond Trace Ratio: Weighted Harmonic Mean of Trace Ratios for Multiclass Discriminant Analysis. IEEE Trans. Knowl. Data Eng. 29(10): 2100-2110 (2017) - [j72]Wenzhang Zhuge, Feiping Nie, Chenping Hou, Dongyun Yi:
Unsupervised Single and Multiple Views Feature Extraction with Structured Graph. IEEE Trans. Knowl. Data Eng. 29(10): 2347-2359 (2017) - [j71]Rui Zhang, Feiping Nie, Xuelong Li:
Regularized Class-Specific Subspace Classifier. IEEE Trans. Neural Networks Learn. Syst. 28(11): 2738-2747 (2017) - [c156]Hongchang Gao, Feiping Nie, Heng Huang:
Local Centroids Structured Non-Negative Matrix Factorization. AAAI 2017: 1905-1911 - [c155]Junwei Han, Kun Song, Feiping Nie, Xuelong Li:
Bilateral k-Means Algorithm for Fast Co-Clustering. AAAI 2017: 1969-1975 - [c154]Xuelong Li, Di Hu, Feiping Nie:
Large Graph Hashing with Spectral Rotation. AAAI 2017: 2203-2209 - [c153]Hanyang Liu, Junwei Han, Feiping Nie, Xuelong Li:
Balanced Clustering with Least Square Regression. AAAI 2017: 2231-2237 - [c152]Yun Liu, Yiming Guo, Hua Wang, Feiping Nie, Heng Huang:
Semi-Supervised Classifications via Elastic and Robust Embedding. AAAI 2017: 2294-2300 - [c151]Minnan Luo, Feiping Nie, Xiaojun Chang, Yi Yang, Alexander G. Hauptmann, Qinghua Zheng:
Probabilistic Non-Negative Matrix Factorization and Its Robust Extensions for Topic Modeling. AAAI 2017: 2308-2314 - [c150]Feiping Nie, Guohao Cai, Xuelong Li:
Multi-View Clustering and Semi-Supervised Classification with Adaptive Neighbours. AAAI 2017: 2408-2414 - [c149]Feiping Nie, Xiaoqian Wang, Heng Huang:
Multiclass Capped ℓp-Norm SVM for Robust Classifications. AAAI 2017: 2415-2421 - [c148]Feiping Nie, Wei Zhu, Xuelong Li:
Unsupervised Large Graph Embedding. AAAI 2017: 2422-2428 - [c147]Kun Song, Feiping Nie, Junwei Han, Xuelong Li:
Parameter Free Large Margin Nearest Neighbor for Distance Metric Learning. AAAI 2017: 2555-2561 - [c146]Xiaowei Xue, Feiping Nie, Sen Wang, Xiaojun Chang, Bela Stantic, Min Yao:
Multi-View Correlated Feature Learning by Uncovering Shared Component. AAAI 2017: 2810-2816 - [c145]Xuelong Li, Mulin Chen, Feiping Nie, Qi Wang:
A Multiview-Based Parameter Free Framework for Group Detection. AAAI 2017: 4147-4153 - [c144]Rui Zhang, Feiping Nie, Xuelong Li:
Embedded clustering via robust orthogonal least square discriminant analysis. ICASSP 2017: 2332-2336 - [c143]Jian'an Zhang, Yuan Yuan, Feiping Nie, Qi Wang:
Largest center-specific margin for dimension reduction. ICASSP 2017: 2352-2356 - [c142]Rui Zhang, Feiping Nie, Xuelong Li:
Semi-supervised classification via both label and side information. ICASSP 2017: 2417-2421 - [c141]Wei Zhu, Feiping Nie, Xuelong Li:
Fast Spectral Clustering with efficient large graph construction. ICASSP 2017: 2492-2496 - [c140]Rui Zhang, Feiping Nie, Xuelong Li:
Auto-weighted two-dimensional principal component analysis with robust outliers. ICASSP 2017: 6065-6069 - [c139]Xiaojun Chen, Joshua Zhexue Huang, Feiping Nie, Renjie Chen, Qingyao Wu:
A Self-Balanced Min-Cut Algorithm for Image Clustering. ICCV 2017: 2080-2088 - [c138]Xiaojun Chen, Feiping Nie, Joshua Zhexue Huang, Min Yang:
Scalable Normalized Cut with Improved Spectral Rotation. IJCAI 2017: 1518-1524 - [c137]Xiaojun Chen, Guowen Yuan, Feiping Nie, Joshua Zhexue Huang:
Semi-supervised Feature Selection via Rescaled Linear Regression. IJCAI 2017: 1525-1531 - [c136]Junwei Han, Kai Xiong, Feiping Nie:
Orthogonal and Nonnegative Graph Reconstruction for Large Scale Clustering. IJCAI 2017: 1809-1815 - [c135]Wenhao Jiang, Cheng Deng, Wei Liu, Feiping Nie, Fu-Lai Chung, Heng Huang:
Theoretic Analysis and Extremely Easy Algorithms for Domain Adaptive Feature Learning. IJCAI 2017: 1958-1964 - [c134]Xuelong Li, Mulin Chen, Feiping Nie, Qi Wang:
Locality Adaptive Discriminant Analysis. IJCAI 2017: 2201-2207 - [c133]Hanyang Liu, Junwei Han, Feiping Nie:
Semi-supervised Orthogonal Graph Embedding with Recursive Projections. IJCAI 2017: 2308-2314 - [c132]Minnan Luo, Lingling Zhang, Feiping Nie, Xiaojun Chang, Buyue Qian, Qinghua Zheng:
Adaptive Semi-Supervised Learning with Discriminative Least Squares Regression. IJCAI 2017: 2421-2427 - [c131]Feiping Nie, Zhouyuan Huo, Heng Huang:
Joint Capped Norms Minimization for Robust Matrix Recovery. IJCAI 2017: 2557-2563 - [c130]Feiping Nie, Jing Li, Xuelong Li:
Self-weighted Multiview Clustering with Multiple Graphs. IJCAI 2017: 2564-2570 - [c129]Tianji Pang, Feiping Nie, Junwei Han:
Flexible Orthogonal Neighborhood Preserving Embedding. IJCAI 2017: 2592-2598 - [c128]Kun Song, Feiping Nie, Junwei Han:
Two dimensional Large Margin Nearest Neighbor for Matrix Classification. IJCAI 2017: 2751-2757 - [c127]Qi Wang, Zequn Qin, Feiping Nie, Yuan Yuan:
Convolutional 2D LDA for Nonlinear Dimensionality Reduction. IJCAI 2017: 2929-2935 - [c126]Qianqian Wang, Quanxue Gao, Xinbo Gao, Feiping Nie:
Angle Principal Component Analysis. IJCAI 2017: 2936-2942 - [c125]Kai Xiong, Feiping Nie, Junwei Han:
Linear Manifold Regularization with Adaptive Graph for Semi-supervised Dimensionality Reduction. IJCAI 2017: 3147-3153 - [c124]Jie Xu, Xianglong Liu, Zhouyuan Huo, Cheng Deng, Feiping Nie, Heng Huang:
Multi-Class Support Vector Machine via Maximizing Multi-Class Margins. IJCAI 2017: 3154-3160 - [c123]Jinglin Xu, Junwei Han, Feiping Nie:
Multi-view Feature Learning with Discriminative Regularization. IJCAI 2017: 3161-3167 - [c122]Jinglin Xu, Feiping Nie, Junwei Han:
Feature Selection via Scaling Factor Integrated Multi-Class Support Vector Machines. IJCAI 2017: 3168-3174 - [c121]Rui Zhang, Feiping Nie, Xuelong Li:
Projected clustering via robust orthogonal least square regression with optimal scaling. IJCNN 2017: 2784-2791 - [c120]Xuelong Li, Di Hu, Feiping Nie:
Deep Binary Reconstruction for Cross-modal Hashing. ACM Multimedia 2017: 1398-1406 - [c119]Feiping Nie, Xiaoqian Wang, Cheng Deng, Heng Huang:
Learning A Structured Optimal Bipartite Graph for Co-Clustering. NIPS 2017: 4129-4138 - [i16]Feiping Nie, Rui Zhang, Xuelong Li:
A generalized power iteration method for solving quadratic problem on the Stiefel manifold. CoRR abs/1701.00381 (2017) - [i15]Mengfan Tang, Feiping Nie, Siripen Pongpaichet, Ramesh C. Jain:
From Photo Streams to Evolving Situations. CoRR abs/1702.05878 (2017) - [i14]Zan Gao, Guotai Zhang, Feiping Nie, Hua Zhang:
Local Shrunk Discriminant Analysis (LSDA). CoRR abs/1705.01206 (2017) - [i13]Xuelong Li, Di Hu, Feiping Nie:
Deep Binary Reconstruction for Cross-modal Hashing. CoRR abs/1708.05127 (2017) - [i12]Yanwei Pang, Bo Zhou, Feiping Nie:
Simultaneously Learning Neighborship and Projection Matrix for Supervised Dimensionality Reduction. CoRR abs/1709.02896 (2017) - 2016
- [j70]Luming Zhang, Yi Yang, Feiping Nie, Ling Shao:
Guest editors' introduction: Perception, Aesthetics, and Emotion in Multimedia Quality Modeling. IEEE Multim. 23(3): 20-22 (2016) - [j69]Qianqian Wang, Fang Chen, Quanxue Gao, Xinbo Gao, Feiping Nie:
On the schatten norm for matrix based subspace learning and classification. Neurocomputing 216: 192-199 (2016) - [j68]Haifeng Zhao, Zheng Wang, Feiping Nie:
Orthogonal least squares regression for feature extraction. Neurocomputing 216: 200-207 (2016) - [j67]Xiaoshuang Shi, Zhenhua Guo, Feiping Nie, Lin Yang, Jane You, Dacheng Tao:
Two-Dimensional Whitening Reconstruction for Enhancing Robustness of Principal Component Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 38(10): 2130-2136 (2016) - [j66]Jingkuan Song, Lianli Gao, Feiping Nie, Heng Tao Shen, Yan Yan, Nicu Sebe:
Optimized Graph Learning Using Partial Tags and Multiple Features for Image and Video Annotation. IEEE Trans. Image Process. 25(11): 4999-5011 (2016) - [j65]Xiaojun Chang, Feiping Nie, Yi Yang, Chengqi Zhang, Heng Huang:
Convex Sparse PCA for Unsupervised Feature Learning. ACM Trans. Knowl. Discov. Data 11(1): 3:1-3:16 (2016) - [j64]Yan Yan, Feiping Nie, Wen Li, Chenqiang Gao, Yi Yang, Dong Xu:
Image Classification by Cross-Media Active Learning With Privileged Information. IEEE Trans. Multim. 18(12): 2494-2502 (2016) - [j63]Haibo He, Nitesh V. Chawla, Huanhuan Chen, Yoonsuck Choe, Andries P. Engelbrecht, Jaya deva, Lyle N. Long, Ali A. Minai, Feiping Nie, Umut Ozertem, Barak A. Pearlmutter, Ling Shao, Jennie Si, Jochen J. Steil, Brijesh K. Verma, Ding Wang:
Editorial IEEE Transactions on Neural Networks and Learning Systems 2016 and Beyond. IEEE Trans. Neural Networks Learn. Syst. 27(1): 1-7 (2016) - [j62]Hong Tao, Chenping Hou, Feiping Nie, Yuanyuan Jiao, Dongyun Yi:
Effective Discriminative Feature Selection With Nontrivial Solution. IEEE Trans. Neural Networks Learn. Syst. 27(4): 796-808 (2016) - [j61]Xiaojun Chang, Feiping Nie, Sen Wang, Yi Yang, Xiaofang Zhou, Chengqi Zhang:
Compound Rank-k Projections for Bilinear Analysis. IEEE Trans. Neural Networks Learn. Syst. 27(7): 1502-1513 (2016) - [c118]Lianli Gao, Jingkuan Song, Feiping Nie, Fuhao Zou, Nicu Sebe, Heng Tao Shen:
Graph-without-cut: An Ideal Graph Learning for Image Segmentation. AAAI 2016: 1188-1194 - [c117]Feiping Nie, Wei Zhu, Xuelong Li:
Unsupervised Feature Selection with Structured Graph Optimization. AAAI 2016: 1302-1308 - [c116]Chenping Hou, Feiping Nie, Dacheng Tao:
Discriminative Vanishing Component Analysis. AAAI 2016: 1666-1672 - [c115]Feiping Nie, Hua Wang, Cheng Deng, Xinbo Gao, Xuelong Li, Heng Huang:
New l1-Norm Relaxations and Optimizations for Graph Clustering. AAAI 2016: 1962-1968 - [c114]Feiping Nie, Xiaoqian Wang, Michael I. Jordan, Heng Huang:
The Constrained Laplacian Rank Algorithm for Graph-Based Clustering. AAAI 2016: 1969-1976 - [c113]Wei Wang, Yan Yan, Feiping Nie, Xavier Alameda-Pineda, Shuicheng Yan, Nicu Sebe:
Projective Unsupervised Flexible Embedding with Optimal Graph. BMVC 2016 - [c112]Rong Quan, Junwei Han, Dingwen Zhang, Feiping Nie:
Object Co-segmentation via Graph Optimized-Flexible Manifold Ranking. CVPR 2016: 687-695 - [c111]Jinglin Xu, Junwei Han, Feiping Nie:
Discriminatively Embedded K-Means for Multi-view Clustering. CVPR 2016: 5356-5364 - [c110]Lina Yao, Feiping Nie, Quan Z. Sheng, Tao Gu, Xue Li, Sen Wang:
Learning from less for better: semi-supervised activity recognition via shared structure discovery. UbiComp 2016: 13-24 - [c109]Baolin Guo, Chenping Hou, Feiping Nie, Dongyun Yi:
Semi-Supervised Multi-label Dimensionality Reduction. ICDM 2016: 919-924 - [c108]De Wang, Feiping Nie, Heng Huang:
Learning Task Relational Structure for Multi-task Feature Learning. ICDM 2016: 1239-1244 - [c107]Mengfan Tang, Pranav Agrawal, Feiping Nie, Siripen Pongpaichet, Ramesh C. Jain:
A graph based multimodal geospatial interpolation framework. ICME 2016: 1-6 - [c106]Liangchen Liu, Feiping Nie, Teng Zhang, Arnold Wiliem, Brian C. Lovell:
Unsupervised automatic attribute discovery method via multi-graph clustering. ICPR 2016: 1713-1718 - [c105]Wenzhang Zhuge, Chenping Hou, Feiping Nie, Dongyun Yi:
Unsupervised feature extraction using a learned graph with clustering structure. ICPR 2016: 3597-3602 - [c104]Shuai Zheng, Feiping Nie, Chris H. Q. Ding, Heng Huang:
A Harmonic Mean Linear Discriminant Analysis for Robust Image Classification. ICTAI 2016: 402-409 - [c103]Minnan Luo, Feiping Nie, Xiaojun Chang, Yi Yang, Alexander G. Hauptmann, Qinghua Zheng:
Avoiding Optimal Mean Robust PCA/2DPCA with Non-greedy ℓ1-Norm Maximization. IJCAI 2016: 1802-1808 - [c102]Feiping Nie, Heng Huang:
Subspace Clustering via New Low-Rank Model with Discrete Group Structure Constraint. IJCAI 2016: 1874-1880 - [c101]Feiping Nie, Jing Li, Xuelong Li:
Parameter-Free Auto-Weighted Multiple Graph Learning: A Framework for Multiview Clustering and Semi-Supervised Classification. IJCAI 2016: 1881-1887 - [c100]De Wang, Feiping Nie, Heng Huang:
Fast Robust Non-Negative Matrix Factorization for Large-Scale Human Action Data Clustering. IJCAI 2016: 2104-2110 - [c99]Jinglin Xu, Junwei Han, Kai Xiong, Feiping Nie:
Robust and Sparse Fuzzy K-Means Clustering. IJCAI 2016: 2224-2230 - [c98]Xiaoqian Wang, Feiping Nie, Heng Huang:
Structured Doubly Stochastic Matrix for Graph Based Clustering: Structured Doubly Stochastic Matrix. KDD 2016: 1245-1254 - [c97]Zhouyuan Huo, Feiping Nie, Heng Huang:
Robust and Effective Metric Learning Using Capped Trace Norm: Metric Learning via Capped Trace Norm. KDD 2016: 1605-1614 - [c96]Zhengxia Wang, Xiaofeng Zhu, Ehsan Adeli, Yingying Zhu, Chen Zu, Feiping Nie, Dinggang Shen, Guorong Wu:
Progressive Graph-Based Transductive Learning for Multi-modal Classification of Brain Disorder Disease. MICCAI (1) 2016: 291-299 - [c95]Mengfan Tang, Feiping Nie, Ramesh C. Jain:
Capped Lp-Norm Graph Embedding for Photo Clustering. ACM Multimedia 2016: 431-435 - [c94]Jingkuan Song, Lianli Gao, Mihai Marian Puscas, Feiping Nie, Fumin Shen, Nicu Sebe:
Joint Graph Learning and Video Segmentation via Multiple Cues and Topology Calibration. ACM Multimedia 2016: 831-840 - [c93]Sen Wang, Feiping Nie, Xiaojun Chang, Xue Li, Quan Z. Sheng, Lina Yao:
Uncovering Locally Discriminative Structure for Feature Analysis. ECML/PKDD (1) 2016: 281-295 - [i11]Feiping Nie, Heng Huang:
Non-Greedy L21-Norm Maximization for Principal Component Analysis. CoRR abs/1603.08293 (2016) - [i10]Sen Wang, Feiping Nie, Xiaojun Chang, Xue Li, Quan Z. Sheng, Lina Yao:
Uncovering Locally Discriminative Structure for Feature Analysis. CoRR abs/1607.02559 (2016) - [i9]Shuai Zheng, Feiping Nie, Chris H. Q. Ding, Heng Huang:
A Harmonic Mean Linear Discriminant Analysis for Robust Image Classification. CoRR abs/1610.04631 (2016) - [i8]Shuai Zheng, Xiao Cai, Chris H. Q. Ding, Feiping Nie, Heng Huang:
A Closed Form Solution to Multi-View Low-Rank Regression. CoRR abs/1610.04668 (2016) - 2015
- [j60]Yi Yang, Zhigang Ma, Feiping Nie, Xiaojun Chang, Alexander G. Hauptmann:
Multi-Class Active Learning by Uncertainty Sampling with Diversity Maximization. Int. J. Comput. Vis. 113(2): 113-127 (2015) - [j59]Feiping Nie, Hua Wang, Heng Huang, Chris H. Q. Ding:
Joint Schatten p-norm and ℓp-norm robust matrix completion for missing value recovery. Knowl. Inf. Syst. 42(3): 525-544 (2015) - [j58]Yang Yang, Zhigang Ma, Yi Yang, Feiping Nie, Heng Tao Shen:
Multitask Spectral Clustering by Exploring Intertask Correlation. IEEE Trans. Cybern. 45(5): 1069-1080 (2015) - [j57]Rong Wang, Feiping Nie, Xiaojun Yang, Feifei Gao, Minli Yao:
Robust 2DPCA With Non-greedy ℓ1-Norm Maximization for Image Analysis. IEEE Trans. Cybern. 45(5): 1108-1112 (2015) - [j56]Hua Wang, Feiping Nie, Heng Huang:
Large-Scale Cross-Language Web Page Classification via Dual Knowledge Transfer Using Fast Nonnegative Matrix Trifactorization. ACM Trans. Knowl. Discov. Data 10(1): 1:1-1:29 (2015) - [j55]De Wang, Feiping Nie, Heng Huang:
Feature Selection via Global Redundancy Minimization. IEEE Trans. Knowl. Data Eng. 27(10): 2743-2755 (2015) - [j54]Chenping Hou, Feiping Nie, Dongyun Yi, Dacheng Tao:
Discriminative Embedded Clustering: A Framework for Grouping High-Dimensional Data. IEEE Trans. Neural Networks Learn. Syst. 26(6): 1287-1299 (2015) - [c92]Shuai Zheng, Xiao Cai, Chris H. Q. Ding, Feiping Nie, Heng Huang:
A Closed Form Solution to Multi-View Low-Rank Regression. AAAI 2015: 1973-1979 - [c91]Xiaojun Chang, Feiping Nie, Zhigang Ma, Yi Yang, Xiaofang Zhou:
A Convex Formulation for Spectral Shrunk Clustering. AAAI 2015: 2532-2538 - [c90]Yeqing Li, Feiping Nie, Heng Huang, Junzhou Huang:
Large-Scale Multi-View Spectral Clustering via Bipartite Graph. AAAI 2015: 2750-2756 - [c89]Hua Wang, Feiping Nie, Heng Huang:
Learning Robust Locality Preserving Projection via p-Order Minimization. AAAI 2015: 3059-3065 - [c88]Hongchang Gao, Feiping Nie, Tom Weidong Cai, Heng Huang:
Robust Capped Norm Nonnegative Matrix Factorization: Capped Norm NMF. CIKM 2015: 871-880 - [c87]Lianli Gao, Jingkuan Song, Feiping Nie, Yan Yan, Nicu Sebe, Heng Tao Shen:
Optimal graph learning with partial tags and multiple features for image and video annotation. CVPR 2015: 4371-4379 - [c86]Hongchang Gao, Feiping Nie, Xuelong Li, Heng Huang:
Multi-view Subspace Clustering. ICCV 2015: 4238-4246 - [c85]Jin Huang, Feiping Nie, Heng Huang:
A New Simplex Sparse Learning Model to Measure Data Similarity for Clustering. IJCAI 2015: 3569-3575 - [c84]Wenhao Jiang, Feiping Nie, Heng Huang:
Robust Dictionary Learning with Capped l1-Norm. IJCAI 2015: 3590-3596 - [c83]Xiaoqian Wang, Yun Liu, Feiping Nie, Heng Huang:
Discriminative Unsupervised Dimensionality Reduction. IJCAI 2015: 3925-3931 - [c82]Hongchang Gao, Chengtao Cai, Jingwen Yan, Lin Yan, Joaquín Goñi Cortes, Yang Wang, Feiping Nie, John D. West, Andrew J. Saykin, Li Shen, Heng Huang:
Identifying Connectome Module Patterns via New Balanced Multi-graph Normalized Cut. MICCAI (2) 2015: 169-176 - [c81]Sen Wang, Feiping Nie, Xiaojun Chang, Lina Yao, Xue Li, Quan Z. Sheng:
Unsupervised Feature Analysis with Class Margin Optimization. ECML/PKDD (1) 2015: 383-398 - [i7]Hong Tao, Chenping Hou, Feiping Nie, Yuanyuan Jiao, Dongyun Yi:
Effective Discriminative Feature Selection with Non-trivial Solutions. CoRR abs/1504.05408 (2015) - [i6]Sen Wang, Feiping Nie, Xiaojun Chang, Lina Yao, Xue Li, Quan Z. Sheng:
Unsupervised Feature Analysis with Class Margin Optimization. CoRR abs/1506.01330 (2015) - [i5]Wenhao Jiang, Feiping Nie, Korris Fu-Lai Chung, Heng Huang:
Algorithm and Theoretical Analysis for Domain Adaptation Feature Learning with Linear Classifiers. CoRR abs/1509.01710 (2015) - 2014
- [j53]Zhigang Ma, Yi Yang, Feiping Nie, Nicu Sebe, Shuicheng Yan, Alexander G. Hauptmann:
Harnessing Lab Knowledge for Real-World Action Recognition. Int. J. Comput. Vis. 109(1-2): 60-73 (2014) - [j52]Guorong Wu, Qian Wang, Daoqiang Zhang, Feiping Nie, Heng Huang, Dinggang Shen:
A generative probability model of joint label fusion for multi-atlas based brain segmentation. Medical Image Anal. 18(6): 881-890 (2014) - [j51]Chenping Hou, Feiping Nie, Hua Wang, Dongyun Yi, Changshui Zhang:
Learning high-dimensional correspondence via manifold learning and local approximation. Neural Comput. Appl. 24(7-8): 1555-1568 (2014) - [j50]Chenping Hou, Feiping Nie, Changshui Zhang, Dongyun Yi, Yi Wu:
Multiple rank multi-linear SVM for matrix data classification. Pattern Recognit. 47(1): 454-469 (2014) - [j49]Chenping Hou, Feiping Nie, Xuelong Li, Dongyun Yi, Yi Wu:
Joint Embedding Learning and Sparse Regression: A Framework for Unsupervised Feature Selection. IEEE Trans. Cybern. 44(6): 793-804 (2014) - [c80]Xiaojun Chang, Feiping Nie, Yi Yang, Heng Huang:
A Convex Formulation for Semi-Supervised Multi-Label Feature Selection. AAAI 2014: 1171-1177 - [c79]Hua Wang, Feiping Nie, Heng Huang:
Globally and Locally Consistent Unsupervised Projection. AAAI 2014: 1328-1333 - [c78]Miao Zhang, Chris H. Q. Ding, Ya Zhang, Feiping Nie:
Feature Selection at the Discrete Limit. AAAI 2014: 1355-1361 - [c77]Hua Wang, Feiping Nie, Heng Huang:
Low-Rank Tensor Completion with Spatio-Temporal Consistency. AAAI 2014: 2846-2852 - [c76]Feiping Nie, Yizhen Huang, Heng Huang:
Linear Time Solver for Primal SVM. ICML 2014: 505-513 - [c75]Feiping Nie, Jianjun Yuan, Heng Huang:
Optimal Mean Robust Principal Component Analysis. ICML 2014: 1062-1070 - [c74]Hua Wang, Feiping Nie, Heng Huang:
Robust Distance Metric Learning via Simultaneous L1-Norm Minimization and Maximization. ICML 2014: 1836-1844 - [c73]De Wang, Feiping Nie, Heng Huang:
Large-scale adaptive semi-supervised learning via unified inductive and transductive model. KDD 2014: 482-491 - [c72]Feiping Nie, Xiaoqian Wang, Heng Huang:
Clustering and projected clustering with adaptive neighbors. KDD 2014: 977-986 - [c71]De Wang, Yang Wang, Feiping Nie, Jingwen Yan, Tom Weidong Cai, Andrew J. Saykin, Li Shen, Heng Huang:
Human Connectome Module Pattern Detection Using a New Multi-graph MinMax Cut Model. MICCAI (3) 2014: 313-320 - [c70]Deguang Kong, Ryohei Fujimaki, Ji Liu, Feiping Nie, Chris H. Q. Ding:
Exclusive Feature Learning on Arbitrary Structures via \ell_{1, 2}-norm. NIPS 2014: 1655-1663 - [c69]De Wang, Feiping Nie, Heng Huang:
Unsupervised Feature Selection via Unified Trace Ratio Formulation and K-means Clustering (TRACK). ECML/PKDD (3) 2014: 306-321 - [c68]Feiping Nie, Xiao Cai, Heng Huang:
Flexible Shift-Invariant Locality and Globality Preserving Projections. ECML/PKDD (2) 2014: 485-500 - [i4]Xiaojun Chang, Haoquan Shen, Feiping Nie, Sen Wang, Yi Yang, Xiaofang Zhou:
Compound Rank-k Projections for Bilinear Analysis. CoRR abs/1411.6231 (2014) - [i3]Xiaojun Chang, Feiping Nie, Yi Yang, Heng Huang:
A Convex Sparse PCA for Feature Analysis. CoRR abs/1411.6233 (2014) - [i2]Xiaojun Chang, Feiping Nie, Zhigang Ma, Yi Yang:
Balanced k-Means and Min-Cut Clustering. CoRR abs/1411.6235 (2014) - [i1]Xiaojun Chang, Feiping Nie, Zhigang Ma, Yi Yang, Xiaofang Zhou:
A Convex Formulation for Spectral Shrunk Clustering. CoRR abs/1411.6308 (2014) - 2013
- [j48]Yun Liu, Feiping Nie, Jigang Wu, Lihui Chen:
Efficient semi-supervised feature selection with noise insensitive trace ratio criterion. Neurocomputing 105: 12-18 (2013) - [j47]Chenping Hou, Feiping Nie, Yuanyuan Jiao, Changshui Zhang, Yi Wu:
Learning a subspace for clustering via pattern shrinking. Inf. Process. Manag. 49(4): 871-883 (2013) - [j46]Hua Wang, Heng Huang, Chris H. Q. Ding, Feiping Nie:
Predicting Protein-Protein Interactions from Multimodal Biological Data Sources via Nonnegative Matrix Tri-Factorization. J. Comput. Biol. 20(4): 344-358 (2013) - [j45]Chenping Hou, Feiping Nie, Dongyun Yi, Yi Wu:
Efficient Image Classification via Multiple Rank Regression. IEEE Trans. Image Process. 22(1): 340-352 (2013) - [j44]Jin Huang, Feiping Nie, Heng Huang, Yi-Cheng Tu, Yu Lei:
Social trust prediction using heterogeneous networks. ACM Trans. Knowl. Discov. Data 7(4): 17:1-17:21 (2013) - [j43]Jin Huang, Feiping Nie, Heng Huang, Chris H. Q. Ding:
Robust Manifold Nonnegative Matrix Factorization. ACM Trans. Knowl. Discov. Data 8(3): 11:1-11:21 (2013) - [c67]Jin Huang, Feiping Nie, Heng Huang:
Robust Discrete Matrix Completion. AAAI 2013: 424-430 - [c66]Jin Huang, Feiping Nie, Heng Huang:
Spectral Rotation versus K-Means in Spectral Clustering. AAAI 2013: 431-437 - [c65]Jin Huang, Feiping Nie, Heng Huang, Chris H. Q. Ding:
Supervised and Projected Sparse Coding for Image Classification. AAAI 2013: 438-444 - [c64]Hua Wang, Feiping Nie, Heng Huang, Chris H. Q. Ding:
Heterogeneous Visual Features Fusion via Sparse Multimodal Machine. CVPR 2013: 3097-3102 - [c63]Xiao Cai, Feiping Nie, Weidong Cai, Heng Huang:
New Graph Structured Sparsity Model for Multi-label Image Annotations. ICCV 2013: 801-808 - [c62]Hua Wang, Feiping Nie, Weidong Cai, Heng Huang:
Semi-supervised Robust Dictionary Learning via Efficient l-Norms Minimization. ICCV 2013: 1145-1152 - [c61]Xiao Cai, Feiping Nie, Weidong Cai, Heng Huang:
Heterogeneous Image Features Integration via Multi-modal Semi-supervised Learning Model. ICCV 2013: 1737-1744 - [c60]Hua Wang, Feiping Nie, Heng Huang:
Robust and Discriminative Self-Taught Learning. ICML (3) 2013: 298-306 - [c59]Hua Wang, Feiping Nie, Heng Huang:
Multi-View Clustering and Feature Learning via Structured Sparsity. ICML (3) 2013: 352-360 - [c58]Xiao Cai, Feiping Nie, Heng Huang:
Exact Top-k Feature Selection via l2, 0-Norm Constraint. IJCAI 2013: 1240-1246 - [c57]Zhigang Ma, Yi Yang, Feiping Nie, Nicu Sebe:
Thinking of Images as What They Are: Compound Matrix Regression for Image Classification. IJCAI 2013: 1530-1536 - [c56]Feiping Nie, Hua Wang, Heng Huang, Chris H. Q. Ding:
Adaptive Loss Minimization for Semi-Supervised Elastic Embedding. IJCAI 2013: 1565-1571 - [c55]Feiping Nie, Hua Wang, Heng Huang, Chris H. Q. Ding:
Early Active Learning via Robust Representation and Structured Sparsity. IJCAI 2013: 1572-1578 - [c54]Xiao Cai, Feiping Nie, Heng Huang:
Multi-View K-Means Clustering on Big Data. IJCAI 2013: 2598-2604 - [c53]Jin Huang, Feiping Nie, Heng Huang, Yu Lei, Chris H. Q. Ding:
Social Trust Prediction Using Rank-k Matrix Recovery. IJCAI 2013: 2647-2653 - [c52]De Wang, Feiping Nie, Heng Huang, Jingwen Yan, Shannon L. Risacher, Andrew J. Saykin, Li Shen:
Structural Brain Network Constrained Neuroimaging Marker Identification for Predicting Cognitive Functions. IPMI 2013: 536-547 - [c51]Xiao Cai, Chris H. Q. Ding, Feiping Nie, Heng Huang:
On the equivalent of low-rank linear regressions and linear discriminant analysis based regressions. KDD 2013: 1124-1132 - [c50]Guorong Wu, Qian Wang, Shu Liao, Daoqiang Zhang, Feiping Nie, Dinggang Shen:
Minimizing Joint Risk of Mislabeling for Iterative Patch-Based Label Fusion. MICCAI (3) 2013: 551-558 - [c49]Heng Huang, Jingwen Yan, Feiping Nie, Jin Huang, Weidong Cai, Andrew J. Saykin, Li Shen:
A New Sparse Simplex Model for Brain Anatomical and Genetic Network Analysis. MICCAI (2) 2013: 625-632 - 2012
- [j42]Hua Wang, Feiping Nie, Heng Huang, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Li Shen:
Identifying quantitative trait loci via group-sparse multitask regression and feature selection: an imaging genetics study of the ADNI cohort. Bioinform. 28(2): 229-237 (2012) - [j41]Hua Wang, Feiping Nie, Heng Huang, Shannon L. Risacher, Andrew J. Saykin, Li Shen:
Identifying disease sensitive and quantitative trait-relevant biomarkers from multidimensional heterogeneous imaging genetics data via sparse multimodal multitask learning. Bioinform. 28(12): 127-136 (2012) - [j40]Hua Wang, Feiping Nie, Heng Huang, Jingwen Yan, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Li Shen:
From phenotype to genotype: an association study of longitudinal phenotypic markers to Alzheimer's disease relevant SNPs. Bioinform. 28(18): 619-625 (2012) - [j39]Shizhun Yang, Chenping Hou, Feiping Nie, Yi Wu:
Unsupervised maximum margin feature selection via L 2, 1-norm minimization. Neural Comput. Appl. 21(7): 1791-1799 (2012) - [j38]Yi Yang, Feiping Nie, Dong Xu, Jiebo Luo, Yueting Zhuang, Yunhe Pan:
A Multimedia Retrieval Framework Based on Semi-Supervised Ranking and Relevance Feedback. IEEE Trans. Pattern Anal. Mach. Intell. 34(4): 723-742 (2012) - [j37]Feiping Nie, Shiming Xiang, Yun Liu, Chenping Hou, Changshui Zhang:
Orthogonal vs. uncorrelated least squares discriminant analysis for feature extraction. Pattern Recognit. Lett. 33(5): 485-491 (2012) - [j36]Yi Huang, Dong Xu, Feiping Nie:
Patch Distribution Compatible Semisupervised Dimension Reduction for Face and Human Gait Recognition. IEEE Trans. Circuits Syst. Video Technol. 22(3): 479-488 (2012) - [j35]Yi Yang, Fei Wu, Feiping Nie, Heng Tao Shen, Yueting Zhuang, Alexander G. Hauptmann:
Web and Personal Image Annotation by Mining Label Correlation With Relaxed Visual Graph Embedding. IEEE Trans. Image Process. 21(3): 1339-1351 (2012) - [j34]Zhigang Ma, Feiping Nie, Yi Yang, Jasper R. R. Uijlings, Nicu Sebe:
Web Image Annotation Via Subspace-Sparsity Collaborated Feature Selection. IEEE Trans. Multim. 14(4): 1021-1030 (2012) - [j33]Zhigang Ma, Feiping Nie, Yi Yang, Jasper R. R. Uijlings, Nicu Sebe, Alexander G. Hauptmann:
Discriminating Joint Feature Analysis for Multimedia Data Understanding. IEEE Trans. Multim. 14(6): 1662-1672 (2012) - [j32]Yi Huang, Dong Xu, Feiping Nie:
Semi-Supervised Dimension Reduction Using Trace Ratio Criterion. IEEE Trans. Neural Networks Learn. Syst. 23(3): 519-526 (2012) - [j31]Shiming Xiang, Feiping Nie, Gaofeng Meng, Chunhong Pan, Changshui Zhang:
Discriminative Least Squares Regression for Multiclass Classification and Feature Selection. IEEE Trans. Neural Networks Learn. Syst. 23(11): 1738-1754 (2012) - [j30]Feiping Nie, Dong Xu, Xuelong Li:
Initialization Independent Clustering With Actively Self-Training Method. IEEE Trans. Syst. Man Cybern. Part B 42(1): 17-27 (2012) - [c48]Feiping Nie, Heng Huang, Chris H. Q. Ding:
Low-Rank Matrix Recovery via Efficient Schatten p-Norm Minimization. AAAI 2012: 655-661 - [c47]Jin Huang, Feiping Nie, Heng Huang, Yi-Cheng Tu:
Trust prediction via aggregating heterogeneous social networks. CIKM 2012: 1774-1778 - [c46]Hua Wang, Feiping Nie, Heng Huang:
Robust and discriminative distance for Multi-Instance Learning. CVPR 2012: 2919-2924 - [c45]Feiping Nie, Hua Wang, Xiao Cai, Heng Huang, Chris H. Q. Ding:
Robust Matrix Completion via Joint Schatten p-Norm and lp-Norm Minimization. ICDM 2012: 566-574 - [c44]Deguang Kong, Chris H. Q. Ding, Heng Huang, Feiping Nie:
An Iterative Locally Linear Embedding Algorithm. ICML 2012 - [c43]Hanbo Chen, Xiao Cai, Dajiang Zhu, Feiping Nie, Tianming Liu, Heng Huang:
Group-Wise Consistent Parcellation of Gyri via Adaptive Multi-view Spectral Clustering of Fiber Shapes. MICCAI (2) 2012: 271-279 - [c42]Hua Wang, Feiping Nie, Heng Huang, Jingwen Yan, Sungeun Kim, Shannon L. Risacher, Andrew J. Saykin, Li Shen:
High-Order Multi-Task Feature Learning to Identify Longitudinal Phenotypic Markers for Alzheimer's Disease Progression Prediction. NIPS 2012: 1286-1294 - [c41]Dijun Luo, Chris H. Q. Ding, Heng Huang, Feiping Nie:
Forging The Graphs: A Low Rank and Positive Semidefinite Graph Learning Approach. NIPS 2012: 2969-2977 - [c40]Hua Wang, Heng Huang, Chris H. Q. Ding, Feiping Nie:
Predicting Protein-Protein Interactions from Multimodal Biological Data Sources via Nonnegative Matrix Tri-Factorization. RECOMB 2012: 314-325 - 2011
- [j29]Cheng Chen, Yi Yang, Feiping Nie, Jean-Marc Odobez:
3D human pose recovery from image by efficient visual feature selection. Comput. Vis. Image Underst. 115(3): 290-299 (2011) - [j28]Shiming Xiang, Chunhong Pan, Feiping Nie, Changshui Zhang:
Interactive Image Segmentation With Multiple Linear Reconstructions in Windows. IEEE Trans. Multim. 13(2): 342-352 (2011) - [j27]Chenping Hou, Feiping Nie, Fei Wang, Changshui Zhang, Yi Wu:
Semisupervised Learning Using Negative Labels. IEEE Trans. Neural Networks 22(3): 420-432 (2011) - [j26]Feiping Nie, Zinan Zeng, Ivor W. Tsang, Dong Xu, Changshui Zhang:
Spectral Embedded Clustering: A Framework for In-Sample and Out-of-Sample Spectral Clustering. IEEE Trans. Neural Networks 22(11): 1796-1808 (2011) - [j25]Feiping Nie, Dong Xu, Xuelong Li, Shiming Xiang:
Semisupervised Dimensionality Reduction and Classification Through Virtual Label Regression. IEEE Trans. Syst. Man Cybern. Part B 41(3): 675-685 (2011) - [j24]Shiming Xiang, Feiping Nie, Chunhong Pan, Changshui Zhang:
Regression Reformulations of LLE and LTSA With Locally Linear Transformation. IEEE Trans. Syst. Man Cybern. Part B 41(5): 1250-1262 (2011) - [j23]Cheng Chen, Yueting Zhuang, Feiping Nie, Yi Yang, Fei Wu, Jun Xiao:
Learning a 3D Human Pose Distance Metric from Geometric Pose Descriptor. IEEE Trans. Vis. Comput. Graph. 17(11): 1676-1689 (2011) - [c39]Hua Wang, Feiping Nie, Heng Huang:
Learning Instance Specific Distance for Multi-Instance Classification. AAAI 2011: 507-512 - [c38]Yi Yang, Heng Tao Shen, Feiping Nie, Rongrong Ji, Xiaofang Zhou:
Nonnegative Spectral Clustering with Discriminative Regularization. AAAI 2011: 555-560 - [c37]Yang Yang, Yi Yang, Zi Huang, Heng Tao Shen, Feiping Nie:
Tag localization with spatial correlations and joint group sparsity. CVPR 2011: 881-888 - [c36]Xiao Cai, Feiping Nie, Heng Huang, Farhad Kamangar:
Heterogeneous image feature integration via multi-modal spectral clustering. CVPR 2011: 1977-1984 - [c35]Hua Wang, Feiping Nie, Heng Huang, Chris H. Q. Ding:
Dyadic transfer learning for cross-domain image classification. ICCV 2011: 551-556 - [c34]Hua Wang, Feiping Nie, Heng Huang, Shannon L. Risacher, Chris H. Q. Ding, Andrew J. Saykin, Li Shen:
Sparse multi-task regression and feature selection to identify brain imaging predictors for memory performance. ICCV 2011: 557-562 - [c33]Feiping Nie, Hua Wang, Heng Huang, Chris H. Q. Ding:
Unsupervised and semi-supervised learning via ℓ1-norm graph. ICCV 2011: 2268-2273 - [c32]Dijun Luo, Chris H. Q. Ding, Heng Huang, Feiping Nie:
Consensus spectral clustering in near-linear time. ICDE 2011: 1079-1090 - [c31]Xiao Cai, Feiping Nie, Heng Huang, Chris H. Q. Ding:
Multi-Class L2, 1-Norm Support Vector Machine. ICDM 2011: 91-100 - [c30]Hua Wang, Feiping Nie, Heng Huang, Chris H. Q. Ding:
Nonnegative Matrix Tri-factorization Based High-Order Co-clustering and Its Fast Implementation. ICDM 2011: 774-783 - [c29]Dijun Luo, Chris H. Q. Ding, Feiping Nie, Heng Huang:
Cauchy Graph Embedding. ICML 2011: 553-560 - [c28]Chenping Hou, Feiping Nie, Dongyun Yi, Yi Wu:
Feature Selection via Joint Embedding Learning and Sparse Regression. IJCAI 2011: 1324-1329 - [c27]Feiping Nie, Heng Huang, Chris H. Q. Ding, Dijun Luo, Hua Wang:
Robust Principal Component Analysis with Non-Greedy l1-Norm Maximization. IJCAI 2011: 1433-1438 - [c26]Hua Wang, Feiping Nie, Heng Huang, Fillia Makedon:
Fast Nonnegative Matrix Tri-Factorization for Large-Scale Data Co-Clustering. IJCAI 2011: 1553-1558 - [c25]Chenping Hou, Feiping Nie, Yi Wu:
Semi-supervised Dimensionality Reduction via Harmonic Functions. MDAI 2011: 91-102 - [c24]Hua Wang, Feiping Nie, Heng Huang, Shannon L. Risacher, Andrew J. Saykin, Li Shen:
Identifying AD-Sensitive and Cognition-Relevant Imaging Biomarkers via Joint Classification and Regression. MICCAI (3) 2011: 115-123 - [c23]Zhigang Ma, Yi Yang, Feiping Nie, Jasper R. R. Uijlings, Nicu Sebe:
Exploiting the entire feature space with sparsity for automatic image annotation. ACM Multimedia 2011: 283-292 - [c22]Hua Wang, Feiping Nie, Heng Huang, Yi Yang:
Learning frame relevance for video classification. ACM Multimedia 2011: 1345-1348 - [c21]Hua Wang, Heng Huang, Farhad Kamangar, Feiping Nie, Chris H. Q. Ding:
Maximum Margin Multi-Instance Learning. NIPS 2011: 1-9 - [c20]Dijun Luo, Feiping Nie, Chris H. Q. Ding, Heng Huang:
Multi-Subspace Representation and Discovery. ECML/PKDD (2) 2011: 405-420 - [c19]Hua Wang, Heng Huang, Feiping Nie, Chris H. Q. Ding:
Cross-language web page classification via dual knowledge transfer using nonnegative matrix tri-factorization. SIGIR 2011: 933-942 - 2010
- [j22]Changshui Zhang, Feiping Nie, Shiming Xiang:
A general kernelization framework for learning algorithms based on kernel PCA. Neurocomputing 73(4-6): 959-967 (2010) - [j21]Fei Wu, Wenhua Wang, Yi Yang, Yueting Zhuang, Feiping Nie:
Classification by semi-supervised discriminative regularization. Neurocomputing 73(10-12): 1641-1651 (2010) - [j20]Dijun Luo, Heng Huang, Chris H. Q. Ding, Feiping Nie:
On the eigenvectors of p-Laplacian. Mach. Learn. 81(1): 37-51 (2010) - [j19]Feiping Nie, Shiming Xiang, Yun Liu, Changshui Zhang:
A general graph-based semi-supervised learning with novel class discovery. Neural Comput. Appl. 19(4): 549-555 (2010) - [j18]Shiming Xiang, Feiping Nie, Changshui Zhang:
Semi-Supervised Classification via Local Spline Regression. IEEE Trans. Pattern Anal. Mach. Intell. 32(11): 2039-2053 (2010) - [j17]Chenping Hou, Changshui Zhang, Yi Wu, Feiping Nie:
Multiple view semi-supervised dimensionality reduction. Pattern Recognit. 43(3): 720-730 (2010) - [j16]Feiping Nie, Dong Xu, Ivor Wai-Hung Tsang, Changshui Zhang:
Flexible Manifold Embedding: A Framework for Semi-Supervised and Unsupervised Dimension Reduction. IEEE Trans. Image Process. 19(7): 1921-1932 (2010) - [j15]Yi Yang, Dong Xu, Feiping Nie, Shuicheng Yan, Yueting Zhuang:
Image Clustering Using Local Discriminant Models and Global Integration. IEEE Trans. Image Process. 19(10): 2761-2773 (2010) - [j14]Shiming Xiang, Chunhong Pan, Feiping Nie, Changshui Zhang:
TurboPixel Segmentation Using Eigen-Images. IEEE Trans. Image Process. 19(11): 3024-3034 (2010) - [c18]Yi Yang, Feiping Nie, Shiming Xiang, Yueting Zhuang, Wenhua Wang:
Local and Global Regressive Mapping for Manifold Learning with Out-of-Sample Extrapolation. AAAI 2010: 649-654 - [c17]Yi Huang, Dong Xu, Feiping Nie:
Regularized Trace Ratio Discriminant Analysis with Patch Distribution Feature for human gait recognition. ICIP 2010: 2449-2452 - [c16]Feiping Nie, Heng Huang, Xiao Cai, Chris H. Q. Ding:
Efficient and Robust Feature Selection via Joint ℓ2, 1-Norms Minimization. NIPS 2010: 1813-1821 - [c15]Feiping Nie, Chris H. Q. Ding, Dijun Luo, Heng Huang:
Improved MinMax Cut Graph Clustering with Nonnegative Relaxation. ECML/PKDD (2) 2010: 451-466
2000 – 2009
- 2009
- [j13]Chunxia Zhang, Shiming Xiang, Feiping Nie, Yangqiu Song:
Nonlinear dimensionality reduction with relative distance comparison. Neurocomputing 72(7-9): 1719-1731 (2009) - [j12]Shiming Xiang, Feiping Nie, Yangqiu Song, Changshui Zhang, Chunxia Zhang:
Embedding new data points for manifold learning via coordinate propagation. Knowl. Inf. Syst. 19(2): 159-184 (2009) - [j11]Changshui Zhang, Feiping Nie, Shiming Xiang, Chenping Hou:
Soft Constraint Harmonic Energy Minimization for Transductive Learning and its Two Interpretations. Neural Process. Lett. 30(2): 89-102 (2009) - [j10]Feiping Nie, Shiming Xiang, Yangqiu Song, Changshui Zhang:
Extracting the optimal dimensionality for local tensor discriminant analysis. Pattern Recognit. 42(1): 105-114 (2009) - [j9]Feiping Nie, Shiming Xiang, Yangqing Jia, Changshui Zhang:
Semi-supervised orthogonal discriminant analysis via label propagation. Pattern Recognit. 42(11): 2615-2627 (2009) - [j8]Chenping Hou, Feiping Nie, Changshui Zhang, Yi Wu:
Learning an Orthogonal and Smooth Subspace for Image Classification. IEEE Signal Process. Lett. 16(4): 303-306 (2009) - [j7]Shiming Xiang, Feiping Nie, Chunxia Zhang, Changshui Zhang:
Interactive Natural Image Segmentation via Spline Regression. IEEE Trans. Image Process. 18(7): 1623-1632 (2009) - [j6]Shiming Xiang, Feiping Nie, Changshui Zhang, Chunxia Zhang:
Nonlinear Dimensionality Reduction with Local Spline Embedding. IEEE Trans. Knowl. Data Eng. 21(9): 1285-1298 (2009) - [j5]Yangqing Jia, Feiping Nie, Changshui Zhang:
Trace Ratio Problem Revisited. IEEE Trans. Neural Networks 20(4): 729-735 (2009) - [c14]Mingjie Qian, Feiping Nie, Changshui Zhang:
Efficient multi-class unlabeled constrained semi-supervised SVM. CIKM 2009: 1665-1668 - [c13]Mingjie Qian, Feiping Nie, Changshui Zhang:
Probabilistic Labeled Semi-supervised SVM. ICDM Workshops 2009: 394-399 - [c12]Feiping Nie, Dong Xu, Ivor W. Tsang, Changshui Zhang:
Spectral Embedded Clustering. IJCAI 2009: 1181-1186 - [c11]Yi Yang, Dong Xu, Feiping Nie, Jiebo Luo, Yueting Zhuang:
Ranking with local regression and global alignment for cross media retrieval. ACM Multimedia 2009: 175-184 - 2008
- [j4]Yangqiu Song, Feiping Nie, Changshui Zhang, Shiming Xiang:
A unified framework for semi-supervised dimensionality reduction. Pattern Recognit. 41(9): 2789-2799 (2008) - [j3]Shiming Xiang, Feiping Nie, Changshui Zhang:
Learning a Mahalanobis distance metric for data clustering and classification. Pattern Recognit. 41(12): 3600-3612 (2008) - [j2]Shiming Xiang, Feiping Nie, Yangqiu Song, Changshui Zhang:
Contour graph based human tracking and action sequence recognition. Pattern Recognit. 41(12): 3653-3664 (2008) - [j1]Yangqiu Song, Feiping Nie, Changshui Zhang:
Semi-supervised sub-manifold discriminant analysis. Pattern Recognit. Lett. 29(13): 1806-1813 (2008) - [c10]Feiping Nie, Shiming Xiang, Yangqing Jia, Changshui Zhang, Shuicheng Yan:
Trace Ratio Criterion for Feature Selection. AAAI 2008: 671-676 - 2007
- [c9]Feiping Nie, Shiming Xiang, Yangqiu Song, Changshui Zhang:
Optimal Dimensionality Discriminant Analysis and Its Application to Image Recognition. CVPR 2007 - [c8]Feiping Nie, Shiming Xiang, Yangqiu Song, Changshui Zhang:
Extracting the Optimal Dimensionality for Discriminant Analysis. ICASSP (2) 2007: 617-620 - [c7]Feiping Nie, Shiming Xiang, Changshui Zhang:
Neighborhood MinMax Projections. IJCAI 2007: 993-998 - [c6]Shiming Xiang, Feiping Nie, Changshui Zhang, Chunxia Zhang:
Interactive Visual Object Extraction Based on Belief Propagation. MMM (1) 2007: 24-33 - [c5]Shiming Xiang, Feiping Nie, Yangqiu Song, Changshui Zhang, Chunxia Zhang:
Embedding New Data Points for Manifold Learning Via Coordinate Propagation. PAKDD 2007: 332-343 - 2006
- [c4]Shiming Xiang, Feiping Nie, Changshui Zhang:
Texture Image Segmentation: An Interactive Framework Based on Adaptive Features and Transductive Learning. ACCV (1) 2006: 216-225 - [c3]Shiming Xiang, Feiping Nie, Changshui Zhang:
Exemplar-Based Human Contour Tracking. ACCV (1) 2006: 338-347 - [c2]Shiming Xiang, Feiping Nie, Changshui Zhang:
Contour Matching Based on Belief Propagation. ACCV (2) 2006: 489-498 - [c1]Shiming Xiang, Feiping Nie, Changshui Zhang, Chunxia Zhang:
Spline Embedding for Nonlinear Dimensionality Reduction. ECML 2006: 825-832
Coauthor Index
Chris Ding
aka: Chris H. Q. Ding
aka: Chris H. Q. Ding
[j347] [j228] [j144] [i26] [i25] [j83] [c156] [c152] [c149] [c135] [c131] [c124] [c119] [j65] [c115] [c114] [c108] [c104] [c102] [c100] [c98] [c97] [i11] [i9] [i8] [j59] [j56] [j55] [c92] [c90] [c89] [c88] [c86] [c85] [c84] [c83] [c82] [i5] [j52] [c80] [c79] [c77] [c76] [c75] [c74] [c73] [c72] [c71] [c69] [c68] [i3] [j46] [j44] [j43] [c67] [c66] [c65] [c64] [c63] [c62] [c61] [c60] [c59] [c58] [c56] [c55] [c54] [c53] [c52] [c51] [c49] [j42] [j41] [j40] [c48] [c47] [c46] [c45] [c44] [c43] [c42] [c41] [c40] [c39] [c36] [c35] [c34] [c33] [c32] [c31] [c30] [c29] [c27] [c26] [c24] [c22] [c21] [c20] [c19] [j20] [c16] [c15]
[j428] [j425] [j424] [j423] [j422] [j418] [j417] [j416] [j415] [j414] [j413] [j412] [j411] [j410] [j406] [j403] [j401] [j400] [j397] [j393] [j391] [j390] [j385] [j384] [j383] [j382] [j381] [j380] [j377] [j376] [j375] [j372] [j368] [j367] [j366] [j363] [j361] [j358] [j357] [j355] [j353] [j351] [j350] [j349] [j347] [j346] [j345] [j344] [j342] [j341] [j339] [j338] [j337] [j336] [j335] [j333] [j332] [j331] [j330] [j329] [c225] [c224] [c223] [c222] [c221] [c219] [i45] [i43] [j327] [j326] [j325] [j324] [j322] [j320] [j318] [j317] [j307] [j306] [j305] [j303] [j302] [j301] [j300] [j299] [j298] [j297] [j295] [j294] [j292] [j288] [j286] [j284] [j283] [j282] [j281] [j278] [j274] [j273] [j272] [j271] [j270] [j269] [j266] [j264] [j263] [j262] [j261] [j260] [c217] [c216] [c215] [c213] [i38] [j256] [j254] [j253] [j250] [j249] [j248] [j244] [j242] [j241] [j240] [j239] [j237] [j236] [j235] [j234] [j233] [j232] [j225] [j223] [j222] [j219] [c209] [c208] [c207] [c206] [c205] [c203] [c202] [i37] [i36] [j209] [j207] [j206] [j205] [j200] [j199] [j195] [j194] [j191] [j190] [j189] [j188] [j187] [j186] [j184] [j183] [j182] [j181] [j177] [j172] [j171] [j170] [c197] [c196] [c195] [c193] [c192] [c191] [c190] [i31] [j164] [j163] [j154] [j153] [j151] [j150] [j149] [j148] [j145] [j142] [j140] [j139] [j138] [j137] [j135] [c187] [c186] [c185] [c184] [c180] [c179] [c175] [i29] [i28] [i27] [i25] [i24] [j133] [j130] [j118] [j115] [j110] [j103] [j101] [j100] [j99] [c169] [c166] [c165] [c164] [c163] [c162] [c161] [c160] [c158] [c157] [i20] [i19] [i18] [i17] [j94] [j91] [j80] [j75] [j71] [c155] [c154] [c153] [c150] [c148] [c147] [c145] [c144] [c142] [c141] [c140] [c134] [c130] [c121] [c120] [i16] [i13] [c117] [c115] [c101] [c86] [j49] [j30] [j25]
[j424] [j423] [j415] [j414] [j413] [j412] [j411] [c226] [j406] [j400] [j397] [j385] [j384] [j382] [j380] [j376] [j375] [j371] [j370] [j368] [j366] [j363] [j358] [j357] [j355] [j353] [j351] [j350] [j349] [j346] [j345] [j344] [j342] [j341] [j339] [j338] [j335] [j332] [j331] [j330] [j329] [c225] [c224] [c221] [c220] [c219] [i45] [i43] [i42] [j327] [j326] [j325] [j324] [j320] [j318] [j317] [j308] [j307] [j306] [j305] [j303] [j301] [j299] [j298] [j297] [j295] [j294] [j292] [j288] [j283] [j282] [j281] [j278] [j273] [j272] [j269] [j266] [j260] [c217] [c216] [c215] [c214] [c213] [c212] [i38] [j256] [j254] [j253] [j250] [j249] [j248] [j246] [j245] [j244] [j242] [j241] [j239] [j237] [j236] [j235] [j234] [j233] [j230] [j224] [j222] [c209] [c208] [c206] [c205] [c203] [c202] [i37] [i36] [j211] [j209] [j207] [j205] [j197] [j196] [j195] [j194] [j190] [j188] [j186] [j182] [j181] [j177] [j171] [c197] [c196] [c195] [c193] [c192] [c191] [c190] [j168] [j161] [j154] [c180] [i30] [i25] [j125] [j121] [j120] [j118] [j117] [j89] [j76] [j57]
a service of 
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-04-25 05:48 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
