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ORCIDZhouchen Lin
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- affiliation (PhD 2000): Peking University, Department of Machine Intelligence, Beijing, China
- affiliation (former): Microsoft Research Asia, Beijing, China
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2020 – today
- 2022
[j111]Jia Li
, Mingqing Xiao, Cong Fang, Yue Dai, Chao Xu, Zhouchen Lin:
Training Neural Networks by Lifted Proximal Operator Machines. IEEE Trans. Pattern Anal. Mach. Intell. 44(6): 3334-3348 (2022)- [i99]Huan Li, Zhouchen Lin:
Restarted Nonconvex Accelerated Gradient Descent: No More Polylogarithmic Factor in the O(ε-7/4) Complexity. CoRR abs/2201.11411 (2022) - [i98]Yibo Yang, Liang Xie, Shixiang Chen, Xiangtai Li, Zhouchen Lin, Dacheng Tao:
Do We Really Need a Learnable Classifier at the End of Deep Neural Network? CoRR abs/2203.09081 (2022) - [i97]Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
A Unified Contrastive Energy-based Model for Understanding the Generative Ability of Adversarial Training. CoRR abs/2203.13455 (2022) - [i96]Yifei Wang, Qi Zhang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap. CoRR abs/2203.13457 (2022) - [i95]Qingyan Meng, Mingqing Xiao, Shen Yan, Yisen Wang, Zhouchen Lin, Zhi-Quan Luo:
Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representation. CoRR abs/2205.00459 (2022) - [i94]Mingjie Li, Hao Kong, Zhouchen Lin:
SymNMF-Net for The Symmetric NMF Problem. CoRR abs/2205.13214 (2022) - [i93]Zenan Ling, Xingyu Xie, Qiuhao Wang, Zongpeng Zhang, Zhouchen Lin:
Global Convergence of Over-parameterized Deep Equilibrium Models. CoRR abs/2205.13814 (2022) - [i92]Yang Hu, Xiyuan Wang, Zhouchen Lin, Pan Li, Muhan Zhang:
Two-Dimensional Weisfeiler-Lehman Graph Neural Networks for Link Prediction. CoRR abs/2206.09567 (2022) - 2021
- [j110]Tiancheng Shen, Yibo Yang, Zhouchen Lin, Mingbin Zhang:
Recurrent learning with clique structures for prostate sparse-view CT artifacts reduction. IET Image Process. 15(3): 648-655 (2021) - [j109]Hanyuan Hang, Zhouchen Lin, Xiaoyu Liu, Hongwei Wen:
Histogram Transform Ensembles for Large-scale Regression. J. Mach. Learn. Res. 22: 95:1-95:87 (2021) - [j108]Hao Kong, Canyi Lu, Zhouchen Lin:
Tensor Q-rank: new data dependent definition of tensor rank. Mach. Learn. 110(7): 1867-1900 (2021) - [j107]Pan Zhou, Canyi Lu, Jiashi Feng, Zhouchen Lin, Shuicheng Yan:
Tensor Low-Rank Representation for Data Recovery and Clustering. IEEE Trans. Pattern Anal. Mach. Intell. 43(5): 1718-1732 (2021) - [j106]Xinbang Zhang, Jianlong Chang, Yiwen Guo, Gaofeng Meng, Shiming Xiang, Zhouchen Lin, Chunhong Pan:
DATA: Differentiable ArchiTecture Approximation With Distribution Guided Sampling. IEEE Trans. Pattern Anal. Mach. Intell. 43(9): 2905-2920 (2021) - [j105]Yuanyuan Liu, Fanhua Shang, Hongying Liu, Lin Kong, Licheng Jiao, Zhouchen Lin:
Accelerated Variance Reduction Stochastic ADMM for Large-Scale Machine Learning. IEEE Trans. Pattern Anal. Mach. Intell. 43(12): 4242-4255 (2021) - [j104]Jianlong Wu, Xingxu Xie, Liqiang Nie, Zhouchen Lin, Hongbin Zha:
Reconstruction regularized low-rank subspace learning for cross-modal retrieval. Pattern Recognit. 113: 107813 (2021) - [j103]Xiangtai Li, Xia Li, Ansheng You, Li Zhang, Guangliang Cheng, Kuiyuan Yang, Yunhai Tong, Zhouchen Lin:
Towards Efficient Scene Understanding via Squeeze Reasoning. IEEE Trans. Image Process. 30: 7050-7063 (2021) - [c119]Yangyang Li, Lin Kong, Fanhua Shang, Yuanyuan Liu, Hongying Liu, Zhouchen Lin:
Learned Extragradient ISTA with Interpretable Residual Structures for Sparse Coding. AAAI 2021: 8501-8509 - [c118]Zhengyang Shen, Tiancheng Shen, Zhouchen Lin, Jinwen Ma:
PDO-eS2CNNs: Partial Differential Operator Based Equivariant Spherical CNNs. AAAI 2021: 9585-9593 - [c117]Xiangtai Li, Hao He, Xia Li, Duo Li, Guangliang Cheng, Jianping Shi, Lubin Weng, Yunhai Tong, Zhouchen Lin:
PointFlow: Flowing Semantics Through Points for Aerial Image Segmentation. CVPR 2021: 4217-4226 - [c116]Yibo Yang, Shan You, Hongyang Li, Fei Wang, Chen Qian, Zhouchen Lin:
Towards Improving the Consistency, Efficiency, and Flexibility of Differentiable Neural Architecture Search. CVPR 2021: 6667-6676 - [c115]Huasong Zhong, Jianlong Wu, Chong Chen, Jianqiang Huang, Minghua Deng, Liqiang Nie, Zhouchen Lin, Xian-Sheng Hua:
Graph Contrastive Clustering. ICCV 2021: 9204-9213 - [c114]Zhengyang Geng, Meng-Hao Guo, Hongxu Chen, Xia Li, Ke Wei, Zhouchen Lin:
Is Attention Better Than Matrix Decomposition? ICLR 2021 - [c113]Ke Sun, Zhanxing Zhu, Zhouchen Lin:
AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models. ICLR 2021 - [c112]Jingyi Cui, Hanyuan Hang, Yisen Wang, Zhouchen Lin:
GBHT: Gradient Boosting Histogram Transform for Density Estimation. ICML 2021: 2233-2243 - [c111]Ruili Feng, Zhouchen Lin, Jiapeng Zhu, Deli Zhao, Jingren Zhou, Zheng-Jun Zha:
Uncertainty Principles of Encoding GANs. ICML 2021: 3240-3251 - [c110]Hongwei Wen, Jingyi Cui, Hanyuan Hang, Jiabin Liu, Yisen Wang, Zhouchen Lin:
Leveraged Weighted Loss for Partial Label Learning. ICML 2021: 11091-11100 - [c109]Nan Ke, Tong Lin, Zhouchen Lin:
Channel-Weighted Squeeze-and-Excitation Networks For Epileptic Seizure Detection. ICTAI 2021: 666-673 - [c108]Lingshen He, Yuxuan Chen, Zhengyang Shen, Yiming Dong, Yisen Wang, Zhouchen Lin:
Efficient Equivariant Network. NeurIPS 2021: 5290-5302 - [c107]Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Dissecting the Diffusion Process in Linear Graph Convolutional Networks. NeurIPS 2021: 5758-5769 - [c106]Yifei Wang, Zhengyang Geng, Feng Jiang, Chuming Li, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Residual Relaxation for Multi-view Representation Learning. NeurIPS 2021: 12104-12115 - [c105]Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Yisen Wang, Zhouchen Lin:
Training Feedback Spiking Neural Networks by Implicit Differentiation on the Equilibrium State. NeurIPS 2021: 14516-14528 - [c104]Zhengyang Geng, Xin-Yu Zhang, Shaojie Bai, Yisen Wang, Zhouchen Lin:
On Training Implicit Models. NeurIPS 2021: 24247-24260 - [c103]Lingshen He, Yiming Dong, Yisen Wang, Dacheng Tao, Zhouchen Lin:
Gauge Equivariant Transformer. NeurIPS 2021: 27331-27343 - [c102]Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Reparameterized Sampling for Generative Adversarial Networks. ECML/PKDD (3) 2021: 494-509 - [c101]Yong Chen, Yuqing Hou, Shu Leng, Qing Zhang, Zhouchen Lin, Dell Zhang:
Long-Tail Hashing. SIGIR 2021: 1328-1338 - [i91]Yibo Yang, Shan You, Hongyang Li, Fei Wang, Chen Qian, Zhouchen Lin:
Towards Improving the Consistency, Efficiency, and Flexibility of Differentiable Neural Architecture Search. CoRR abs/2101.11342 (2021) - [i90]Risheng Liu, Jiaxin Gao, Jin Zhang, Deyu Meng, Zhouchen Lin:
Investigating Bi-Level Optimization for Learning and Vision from a Unified Perspective: A Survey and Beyond. CoRR abs/2101.11517 (2021) - [i89]Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Dissecting the Diffusion Process in Linear Graph Convolutional Networks. CoRR abs/2102.10739 (2021) - [i88]Xiangtai Li, Hao He, Xia Li, Duo Li, Guangliang Cheng, Jianping Shi, Lubin Weng, Yunhai Tong, Zhouchen Lin:
PointFlow: Flowing Semantics Through Points for Aerial Image Segmentation. CoRR abs/2103.06564 (2021) - [i87]Huasong Zhong, Jianlong Wu, Chong Chen, Jianqiang Huang, Minghua Deng, Liqiang Nie, Zhouchen Lin, Xian-Sheng Hua:
Graph Contrastive Clustering. CoRR abs/2104.01429 (2021) - [i86]Huan Li, Zhouchen Lin:
Accelerated Gradient Tracking over Time-varying Graphs for Decentralized Optimization. CoRR abs/2104.02596 (2021) - [i85]Zhengyang Shen, Tiancheng Shen, Zhouchen Lin, Jinwen Ma:
PDO-eS2CNNs: Partial Differential Operator Based Equivariant Spherical CNNs. CoRR abs/2104.03584 (2021) - [i84]Xingyu Xie, Qiuhao Wang, Zenan Ling, Xia Li, Yisen Wang, Guangcan Liu, Zhouchen Lin:
Optimization Induced Equilibrium Networks. CoRR abs/2105.13228 (2021) - [i83]Hanyuan Hang, Tao Huang, Yuchao Cai, Hanfang Yang, Zhouchen Lin:
Gradient Boosted Binary Histogram Ensemble for Large-scale Regression. CoRR abs/2106.01986 (2021) - [i82]Hongwei Wen, Jingyi Cui, Hanyuan Hang, Jiabin Liu, Yisen Wang, Zhouchen Lin:
Leveraged Weighted Loss for Partial Label Learning. CoRR abs/2106.05731 (2021) - [i81]Jingyi Cui, Hanyuan Hang, Yisen Wang, Zhouchen Lin:
GBHT: Gradient Boosting Histogram Transform for Density Estimation. CoRR abs/2106.05738 (2021) - [i80]Qigong Sun, Xiufang Li, Fanhua Shang, Hongying Liu, Kang Yang, Licheng Jiao, Zhouchen Lin:
Quantized Neural Networks via {-1, +1} Encoding Decomposition and Acceleration. CoRR abs/2106.09886 (2021) - [i79]Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Reparameterized Sampling for Generative Adversarial Networks. CoRR abs/2107.00352 (2021) - [i78]Hanyuan Hang, Yuchao Cai, Hanfang Yang, Zhouchen Lin:
Under-bagging Nearest Neighbors for Imbalanced Classification. CoRR abs/2109.00531 (2021) - [i77]Zhengyang Geng, Meng-Hao Guo, Hongxu Chen, Xia Li, Ke Wei, Zhouchen Lin:
Is Attention Better Than Matrix Decomposition? CoRR abs/2109.04553 (2021) - [i76]Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Yisen Wang, Zhouchen Lin:
Training Feedback Spiking Neural Networks by Implicit Differentiation on the Equilibrium State. CoRR abs/2109.14247 (2021) - [i75]Yifei Wang, Zhengyang Geng, Feng Jiang, Chuming Li, Yisen Wang, Jiansheng Yang, Zhouchen Lin:
Residual Relaxation for Multi-view Representation Learning. CoRR abs/2110.15348 (2021) - [i74]Ke Sun, Mingjie Li, Zhouchen Lin:
Pareto Adversarial Robustness: Balancing Spatial Robustness and Sensitivity-based Robustness. CoRR abs/2111.01996 (2021) - [i73]Zhengyang Geng, Xin-Yu Zhang, Shaojie Bai, Yisen Wang, Zhouchen Lin:
On Training Implicit Models. CoRR abs/2111.05177 (2021) - 2020
- [b1]Zhouchen Lin, Huan Li, Cong Fang:
Accelerated Optimization for Machine Learning - First-Order Algorithms. Springer 2020, ISBN 978-981-15-2909-2, pp. 1-275 - [j102]Huan Li, Zhouchen Lin:
On the Complexity Analysis of the Primal Solutions for the Accelerated Randomized Dual Coordinate Ascent. J. Mach. Learn. Res. 21: 33:1-33:45 (2020) - [j101]Huan Li, Zhouchen Lin:
Provable accelerated gradient method for nonconvex low rank optimization. Mach. Learn. 109(1): 103-134 (2020) - [j100]Canyi Lu, Jiashi Feng, Yudong Chen, Wei Liu, Zhouchen Lin, Shuicheng Yan:
Tensor Robust Principal Component Analysis with a New Tensor Nuclear Norm. IEEE Trans. Pattern Anal. Mach. Intell. 42(4): 925-938 (2020) - [j99]Risheng Liu, Shichao Cheng, Yi He, Xin Fan, Zhouchen Lin, Zhongxuan Luo:
On the Convergence of Learning-Based Iterative Methods for Nonconvex Inverse Problems. IEEE Trans. Pattern Anal. Mach. Intell. 42(12): 3027-3039 (2020) - [j98]Huan Li, Cong Fang, Zhouchen Lin:
Accelerated First-Order Optimization Algorithms for Machine Learning. Proc. IEEE 108(11): 2067-2082 (2020) - [j97]Huan Li, Zhouchen Lin:
Revisiting EXTRA for Smooth Distributed Optimization. SIAM J. Optim. 30(3): 1795-1821 (2020) - [j96]Yinwei Wei, Xiang Wang, Weili Guan, Liqiang Nie, Zhouchen Lin, Baoquan Chen:
Neural Multimodal Cooperative Learning Toward Micro-Video Understanding. IEEE Trans. Image Process. 29: 1-14 (2020) - [j95]Huan Li, Cong Fang, Wotao Yin, Zhouchen Lin:
Decentralized Accelerated Gradient Methods With Increasing Penalty Parameters. IEEE Trans. Signal Process. 68: 4855-4870 (2020) - [c100]Ke Sun, Zhouchen Lin, Zhanxing Zhu:
Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labeled Nodes. AAAI 2020: 5892-5899 - [c99]Jianlong Wu, Xingyu Xie, Liqiang Nie, Zhouchen Lin, Hongbin Zha:
Unified Graph and Low-Rank Tensor Learning for Multi-View Clustering. AAAI 2020: 6388-6395 - [c98]Yibo Yang, Jianlong Wu, Hongyang Li, Xia Li, Tiancheng Shen, Zhouchen Lin:
Dynamical System Inspired Adaptive Time Stepping Controller for Residual Network Families. AAAI 2020: 6648-6655 - [c97]Yueying Kao, Weiming Li, Qiang Wang, Zhouchen Lin, Wooshik Kim, Sunghoon Hong:
Synthetic Depth Transfer for Monocular 3D Object Pose Estimation in the Wild. AAAI 2020: 11221-11228 - [c96]Yibo Yang, Hongyang Li, Xia Li, Qijie Zhao, Jianlong Wu, Zhouchen Lin:
SOGNet: Scene Overlap Graph Network for Panoptic Segmentation. AAAI 2020: 12637-12644 - [c95]Xia Li, Yibo Yang, Qijie Zhao, Tiancheng Shen, Zhouchen Lin, Hong Liu:
Spatial Pyramid Based Graph Reasoning for Semantic Segmentation. CVPR 2020: 8947-8956 - [c94]Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu:
Invertible Image Rescaling. ECCV (1) 2020: 126-144 - [c93]Xiangtai Li, Xia Li, Li Zhang, Guangliang Cheng, Jianping Shi, Zhouchen Lin, Shaohua Tan, Yunhai Tong:
Improving Semantic Segmentation via Decoupled Body and Edge Supervision. ECCV (17) 2020: 435-452 - [c92]Yuchao Cai, Hanyuan Hang, Hanfang Yang, Zhouchen Lin:
Boosted Histogram Transform for Regression. ICML 2020: 1251-1261 - [c91]Mingjie Li, Lingshen He, Zhouchen Lin:
Implicit Euler Skip Connections: Enhancing Adversarial Robustness via Numerical Stability. ICML 2020: 5874-5883 - [c90]Zhengyang Shen, Lingshen He, Zhouchen Lin, Jinwen Ma:
PDO-eConvs: Partial Differential Operator Based Equivariant Convolutions. ICML 2020: 8697-8706 - [c89]Xingyu Xie, Hao Kong, Jianlong Wu, Wayne Zhang, Guangcan Liu, Zhouchen Lin:
Maximum-and-Concatenation Networks. ICML 2020: 10483-10494 - [c88]Yibo Yang, Hongyang Li, Shan You, Fei Wang, Chen Qian, Zhouchen Lin:
ISTA-NAS: Efficient and Consistent Neural Architecture Search by Sparse Coding. NeurIPS 2020 - [i72]Huan Li, Zhouchen Lin:
Revisiting EXTRA for Smooth Distributed Optimization. CoRR abs/2002.10110 (2020) - [i71]Xia Li, Yibo Yang, Qijie Zhao, Tiancheng Shen, Zhouchen Lin, Hong Liu:
Spatial Pyramid Based Graph Reasoning for Semantic Segmentation. CoRR abs/2003.10211 (2020) - [i70]Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu:
Invertible Image Rescaling. CoRR abs/2005.05650 (2020) - [i69]Bing Yu, Ke Sun, He Wang, Zhouchen Lin, Zhanxing Zhu:
Classify and Generate Reciprocally: Simultaneous Positive-Unlabelled Learning and Conditional Generation with Extra Data. CoRR abs/2006.07841 (2020) - [i68]Xingyu Xie, Hao Kong, Jianlong Wu, Wayne Zhang, Guangcan Liu, Zhouchen Lin:
Maximum-and-Concatenation Networks. CoRR abs/2007.04630 (2020) - [i67]Xiangtai Li, Xia Li, Li Zhang, Guangliang Cheng, Jianping Shi, Zhouchen Lin, Shaohua Tan, Yunhai Tong:
Improving Semantic Segmentation via Decoupled Body and Edge Supervision. CoRR abs/2007.10035 (2020) - [i66]Zhengyang Shen, Lingshen He, Zhouchen Lin, Jinwen Ma:
PDO-eConvs: Partial Differential Operator Based Equivariant Convolutions. CoRR abs/2007.10408 (2020) - [i65]Huan Li, Zhouchen Lin, Yongchun Fang:
Optimal Accelerated Variance Reduced EXTRA and DIGing for Strongly Convex and Smooth Decentralized Optimization. CoRR abs/2009.04373 (2020) - [i64]Yibo Yang, Hongyang Li, Shan You, Fei Wang, Chen Qian, Zhouchen Lin:
ISTA-NAS: Efficient and Consistent Neural Architecture Search by Sparse Coding. CoRR abs/2010.06176 (2020) - [i63]Xiangtai Li, Xia Li, Ansheng You, Li Zhang, Guangliang Cheng, Kuiyuan Yang, Yunhai Tong, Zhouchen Lin:
Towards Efficient Scene Understanding via Squeeze Reasoning. CoRR abs/2011.03308 (2020) - [i62]Risheng Liu, Zhu Liu, Pan Mu, Zhouchen Lin, Xin Fan, Zhongxuan Luo:
Learning Optimization-inspired Image Propagation with Control Mechanisms and Architecture Augmentations for Low-level Vision. CoRR abs/2012.05435 (2020)
2010 – 2019
- 2019
- [j94]Gaopeng Jian, Zhouchen Lin, Rongquan Feng:
Two-weight and three-weight linear codes based on Weil sums. Finite Fields Their Appl. 57: 92-107 (2019) - [j93]Huan Li, Zhouchen Lin:
Accelerated Alternating Direction Method of Multipliers: An Optimal O(1 / K) Nonergodic Analysis. J. Sci. Comput. 79(2): 671-699 (2019) - [j92]Zhisheng Zhong, Fangyin Wei, Zhouchen Lin, Chao Zhang:
ADA-Tucker: Compressing deep neural networks via adaptive dimension adjustment tucker decomposition. Neural Networks 110: 104-115 (2019) - [j91]Canyi Lu, Jiashi Feng, Zhouchen Lin, Tao Mei, Shuicheng Yan:
Subspace Clustering by Block Diagonal Representation. IEEE Trans. Pattern Anal. Mach. Intell. 41(2): 487-501 (2019) - [j90]Chunyu Wang, Yizhou Wang, Zhouchen Lin, Alan L. Yuille:
Robust 3D Human Pose Estimation from Single Images or Video Sequences. IEEE Trans. Pattern Anal. Mach. Intell. 41(5): 1227-1241 (2019) - [j89]Baohua Li, Huchuan Lu, Ying Zhang, Zhouchen Lin, Wei Wu:
Subspace Clustering Under Complex Noise. IEEE Trans. Circuits Syst. Video Technol. 29(4): 930-940 (2019) - [j88]Yan Zheng, Zhouchen Lin:
The Augmented Homogeneous Coordinates Matrix-Based Projective Mismatch Removal for Partial-Duplicate Image Search. IEEE Trans. Image Process. 28(1): 181-193 (2019) - [j87]Jianlong Wu, Zhouchen Lin, Hongbin Zha:
Essential Tensor Learning for Multi-View Spectral Clustering. IEEE Trans. Image Process. 28(12): 5910-5922 (2019) - [j86]Wenming Zheng, Cheng Lu, Zhouchen Lin, Tong Zhang, Zhen Cui, Wankou Yang:
ℓ1-Norm Heteroscedastic Discriminant Analysis Under Mixture of Gaussian Distributions. IEEE Trans. Neural Networks Learn. Syst. 30(10): 2898-2915 (2019) - [c87]Jia Li, Cong Fang, Zhouchen Lin:
Lifted Proximal Operator Machines. AAAI 2019: 4181-4188 - [c86]Cong Fang, Zhouchen Lin, Tong Zhang:
Sharp Analysis for Nonconvex SGD Escaping from Saddle Points. COLT 2019: 1192-1234 - [c85]Junjian Zhang, Chun-Guang Li, Chong You, Xianbiao Qi, Honggang Zhang, Jun Guo, Zhouchen Lin:
Self-Supervised Convolutional Subspace Clustering Network. CVPR 2019: 5473-5482 - [c84]Jianlong Wu, Keyu Long, Fei Wang, Chen Qian, Cheng Li, Zhouchen Lin, Hongbin Zha:
Deep Comprehensive Correlation Mining for Image Clustering. ICCV 2019: 8149-8158 - [c83]Xia Li, Zhisheng Zhong, Jianlong Wu, Yibo Yang, Zhouchen Lin, Hong Liu:
Expectation-Maximization Attention Networks for Semantic Segmentation. ICCV 2019: 9166-9175 - [c82]Xingyu Xie, Jianlong Wu, Guangcan Liu, Zhisheng Zhong, Zhouchen Lin:
Differentiable Linearized ADMM. ICML 2019: 6902-6911 - [c81]Tiancheng Shen, Xia Li, Zhisheng Zhong, Jianlong Wu, Zhouchen Lin:
R ^2 2 -Net: Recurrent and Recursive Network for Sparse-View CT Artifacts Removal. MICCAI (6) 2019: 319-327 - [c80]Ke Sun, Zhouchen Lin, Hantao Guo, Zhanxing Zhu:
Virtual Adversarial Training on Graph Convolutional Networks in Node Classification. PRCV (1) 2019: 431-443 - [c79]Lingshen He, Xingyu Xie, Zhouchen Lin:
Neural Ordinary Differential Equations with Envolutionary Weights. PRCV (1) 2019: 598-610 - [e3]Zhouchen Lin, Liang Wang, Jian Yang, Guangming Shi, Tieniu Tan, Nanning Zheng, Xilin Chen, Yanning Zhang:
Pattern Recognition and Computer Vision - Second Chinese Conference, PRCV 2019, Xi'an, China, November 8-11, 2019, Proceedings, Part I. Lecture Notes in Computer Science 11857, Springer 2019, ISBN 978-3-030-31653-2 [contents] - [e2]Zhouchen Lin, Liang Wang, Jian Yang, Guangming Shi, Tieniu Tan, Nanning Zheng, Xilin Chen, Yanning Zhang:
Pattern Recognition and Computer Vision - Second Chinese Conference, PRCV 2019, Xi'an, China, November 8-11, 2019, Proceedings, Part II. Lecture Notes in Computer Science 11858, Springer 2019, ISBN 978-3-030-31722-5 [contents] - [e1]Zhouchen Lin, Liang Wang, Jian Yang, Guangming Shi, Tieniu Tan, Nanning Zheng, Xilin Chen, Yanning Zhang:
Pattern Recognition and Computer Vision - Second Chinese Conference, PRCV 2019, Xi'an, China, November 8-11, 2019, Proceedings, Part III. Lecture Notes in Computer Science 11859, Springer 2019, ISBN 978-3-030-31725-6 [contents] - [i61]Cong Fang, Zhouchen Lin, Tong Zhang:
Sharp Analysis for Nonconvex SGD Escaping from Saddle Points. CoRR abs/1902.00247 (2019) - [i60]Ke Sun, Zhanxing Zhu, Zhouchen Lin:
Towards Understanding Adversarial Examples Systematically: Exploring Data Size, Task and Model Factors. CoRR abs/1902.11019 (2019) - [i59]Ke Sun, Zhanxing Zhu, Zhouchen Lin:
Enhancing the Robustness of Deep Neural Networks by Boundary Conditional GAN. CoRR abs/1902.11029 (2019) - [i58]Ke Sun, Zhanxing Zhu, Zhouchen Lin:
Multi-Stage Self-Supervised Learning for Graph Convolutional Networks. CoRR abs/1902.11038 (2019) - [i57]Ke Sun, Hantao Guo, Zhanxing Zhu, Zhouchen Lin:
Virtual Adversarial Training on Graph Convolutional Networks in Node Classification. CoRR abs/1902.11045 (2019) - [i56]Jianlong Wu, Keyu Long, Fei Wang, Chen Qian, Cheng Li, Zhouchen Lin, Hongbin Zha:
Deep Comprehensive Correlation Mining for Image Clustering. CoRR abs/1904.06925 (2019) - [i55]Junjian Zhang, Chun-Guang Li, Chong You, Xianbiao Qi, Honggang Zhang, Jun Guo, Zhouchen Lin:
Self-Supervised Convolutional Subspace Clustering Network. CoRR abs/1905.00149 (2019) - [i54]Xingyu Xie, Jianlong Wu, Zhisheng Zhong, Guangcan Liu, Zhouchen Lin:
Differentiable Linearized ADMM. CoRR abs/1905.06179 (2019) - [i53]Zhisheng Zhong, Fangyin Wei, Zhouchen Lin, Chao Zhang:
ADA-Tucker: Compressing Deep Neural Networks via Adaptive Dimension Adjustment Tucker Decomposition. CoRR abs/1906.07671 (2019) - [i52]Xia Li, Zhisheng Zhong, Jianlong Wu, Yibo Yang, Zhouchen Lin, Hong Liu:
Expectation-Maximization Attention Networks for Semantic Segmentation. CoRR abs/1907.13426 (2019) - [i51]Ke Sun, Zhouchen Lin, Zhanxing Zhu:
AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models. CoRR abs/1908.05081 (2019) - [i50]Hao Kong, Zhouchen Lin:
Tensor Q-Rank: A New Data Dependent Tensor Rank. CoRR abs/1910.12016 (2019) - [i49]Yibo Yang, Hongyang Li, Xia Li, Qijie Zhao, Jianlong Wu, Zhouchen Lin:
SOGNet: Scene Overlap Graph Network for Panoptic Segmentation. CoRR abs/1911.07527 (2019) - [i48]Ke Sun, Bing Yu, Zhouchen Lin, Zhanxing Zhu:
Patch-level Neighborhood Interpolation: A General and Effective Graph-based Regularization Strategy. CoRR abs/1911.09307 (2019) - [i47]Yibo Yang, Jianlong Wu, Hongyang Li, Xia Li, Tiancheng Shen, Zhouchen Lin:
Dynamical System Inspired Adaptive Time Stepping Controller for Residual Network Families. CoRR abs/1911.10305 (