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Xiaoqian Wang 0001
Person information
- affiliation: Purdue University, West Lafayette, USA
Other persons with the same name
- Xiaoqian Wang 0002 — Tianjin University, Tianjin, China
- Xiaoqian Wang 0003 — China Mobile Research Institute, Beijing, China
- Xiaoqian Wang 0004 — Tsinghua University, Beijing, China (and 1 more)
- Xiaoqian Wang 0005
— Hubei University of Economics, Wuhan, China
- Xiaoqian Wang 0006 — Peking University, Beijing, China
- Xiaoqian Wang 0007 — Hefei University of Technology, Hefei, China
- Xiaoqian Wang 0008 — Jiangsu University, Zhenjiang, China
- Xiaoqian Wang 0009 — Soochow University, Suzhou, Jiangsu, China
- Xiaoqian Wang 0010 — School of electronic and information engineering, Shaanxi Key Lab of Satellite-Terrestrial Network Tech., R&D Xi'an, China
- Xiaoqian Wang 0011 — University of Oklahoma, School of Industrial Engineering, Norman, OK, USA
- Xiaoqian Wang 0012 — Jilin University, School of Economics, Changchun, China
- Xiaoqian Wang 0013 — Nanchang University, Department of Electronic Information Engineering, China
- Xiaoqian Wang 0014
— Beihang University, Beijing, China
- Xiaoqian Wang 0015
— Changchun University of Science and Technology, Department of Physics, China
- Xiaoqian Wang 0016 — Zhejiang Provincial Military Command, Hangzhou, China
- Xiaoqian Wang 0017 — Beijing University of Posts and Telecommunication, School of Electrionic Engineering, China
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2020 – today
- 2024
- [c36]Tianchun Li, Chengxiang Wu, Pengyi Shi, Xiaoqian Wang:
Cumulative Difference Learning VAE for Time-Series with Temporally Correlated Inflow-Outflow. AAAI 2024: 13619-13627 - [c35]Taeuk Jang, Xiaoqian Wang, Heng Huang:
Adversarial Fairness Network. AAAI 2024: 22159-22166 - [c34]Taeuk Jang, Hongchang Gao, Pengyi Shi, Xiaoqian Wang:
Achieving Fairness through Separability: A Unified Framework for Fair Representation Learning. AISTATS 2024: 28-36 - [c33]Yipei Wang, Xiaoqian Wang:
On the Effect of Key Factors in Spurious Correlation: A theoretical Perspective. AISTATS 2024: 3745-3753 - [c32]Shenyu Lu, Yipei Wang, Xiaoqian Wang:
Debiasing Attention Mechanism in Transformer without Demographics. ICLR 2024 - [c31]Shenyu Lu, Junyi Chai, Xiaoqian Wang:
Neural Collapse Inspired Debiased Representation Learning for Min-max Fairness. KDD 2024: 2048-2059 - [i16]Yipei Wang, Bing He, Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, Xiaoqian Wang:
Learning the irreversible progression trajectory of Alzheimer's disease. CoRR abs/2403.06087 (2024) - [i15]Xidong Wu, Shangqian Gao, Zeyu Zhang, Zhenzhen Li, Runxue Bao, Yanfu Zhang, Xiaoqian Wang, Heng Huang:
Auto-Train-Once: Controller Network Guided Automatic Network Pruning from Scratch. CoRR abs/2403.14729 (2024) - [i14]Xiaoze Liu, Feijie Wu, Tianyang Xu, Zhuo Chen, Yichi Zhang, Xiaoqian Wang, Jing Gao:
Evaluating the Factuality of Large Language Models using Large-Scale Knowledge Graphs. CoRR abs/2404.00942 (2024) - [i13]Xiaoze Liu, Ting Sun, Tianyang Xu, Feijie Wu, Cunxiang Wang, Xiaoqian Wang, Jing Gao:
SHIELD: Evaluation and Defense Strategies for Copyright Compliance in LLM Text Generation. CoRR abs/2406.12975 (2024) - 2023
- [j5]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) - [c30]Tianci Liu, Haoyu Wang, Yaqing Wang, Xiaoqian Wang, Lu Su, Jing Gao:
SimFair: A Unified Framework for Fairness-Aware Multi-Label Classification. AAAI 2023: 14338-14346 - [c29]Taeuk Jang, Xiaoqian Wang:
Difficulty-Based Sampling for Debiased Contrastive Representation Learning. CVPR 2023: 24039-24048 - [i12]Tianci Liu, Haoyu Wang, Yaqing Wang, Xiaoqian Wang, Lu Su, Jing Gao:
SimFair: A Unified Framework for Fairness-Aware Multi-Label Classification. CoRR abs/2302.09683 (2023) - [i11]Junyi Chai, Xiaoqian Wang:
To be Robust and to be Fair: Aligning Fairness with Robustness. CoRR abs/2304.00061 (2023) - [i10]Hong Qin, Jude Kong, Wandi Ding, Ramneek Ahluwalia, Christo El-Morr, Zeynep Engin, Jake Okechukwu Effoduh, Rebecca Hwa
, Serena Jingchuan Guo, Laleh Seyyed-Kalantari, Sylvia Kiwuwa Muyingo, Candace Makeda Moore, Ravi Parikh, Reva Schwartz, Dongxiao Zhu, Xiaoqian Wang, Yiye Zhang:
Towards Trustworthy Artificial Intelligence for Equitable Global Health. CoRR abs/2309.05088 (2023) - 2022
- [c28]Taeuk Jang, Pengyi Shi, Xiaoqian Wang:
Group-Aware Threshold Adaptation for Fair Classification. AAAI 2022: 6988-6995 - [c27]Junyi Chai, Xiaoqian Wang:
Fairness with Adaptive Weights. ICML 2022: 2853-2866 - [c26]Junyi Chai, Taeuk Jang, Xiaoqian Wang:
Fairness without Demographics through Knowledge Distillation. NeurIPS 2022 - [c25]Junyi Chai, Xiaoqian Wang:
Self-Supervised Fair Representation Learning without Demographics. NeurIPS 2022 - [c24]Yipei Wang, Xiaoqian Wang:
"Why Not Other Classes?": Towards Class-Contrastive Back-Propagation Explanations. NeurIPS 2022 - [i9]Yipei Wang, Xiaoqian Wang:
A Unified Study of Machine Learning Explanation Evaluation Metrics. CoRR abs/2203.14265 (2022) - 2021
- [c23]Taeuk Jang, Feng Zheng, Xiaoqian Wang:
Constructing a Fair Classifier with Generated Fair Data. AAAI 2021: 7908-7916 - [c22]Xiaoqian Wang, Feiping Nie:
Multi-Task Learning Via Sharing Inexact Low-Rank Subspace. ICASSP 2021: 3690-3694 - [c21]Rui Wang, Xiaoqian Wang, David I. Inouye
:
Shapley Explanation Networks. ICLR 2021 - [c20]Hongchang Gao, Xiaoqian Wang, Lei Luo, Xinghua Shi:
On the Convergence of Stochastic Compositional Gradient Descent Ascent Method. IJCAI 2021: 2389-2395 - [c19]Yipei Wang, Xiaoqian Wang:
Self-Interpretable Model with Transformation Equivariant Interpretation. NeurIPS 2021: 2359-2372 - [i8]Rui Wang, Xiaoqian Wang, David I. Inouye:
Shapley Explanation Networks. CoRR abs/2104.02297 (2021) - [i7]Taeuk Jang, Pengyi Shi, Xiaoqian Wang:
Group-Aware Threshold Adaptation for Fair Classification. CoRR abs/2111.04271 (2021) - [i6]Yipei Wang, Xiaoqian Wang:
Self-Interpretable Model with TransformationEquivariant Interpretation. CoRR abs/2111.04927 (2021) - 2020
- [c18]Yawen Huang, Feng Zheng, Danyang Wang, Junyu Jiang, Xiaoqian Wang, Ling Shao:
Super-Resolution and Inpainting with Degraded and Upgraded Generative Adversarial Networks. IJCAI 2020: 645-651 - [i5]Haoyan Xu, Ziheng Duan, Yida Huang, Jie Feng, Anni Ren, Qianru Zhang, Pengyu Song, Xiaoqian Wang:
Parallel Extraction of Long-term Trends and Short-term Fluctuation Framework for Multivariate Time Series Forecasting. CoRR abs/2008.07730 (2020) - [i4]Yida Huang, Haoyan Xu, Ziheng Duan, Anni Ren, Jie Feng, Qianru Zhang, Xiaoqian Wang:
Modeling Complex Spatial Patterns with Temporal Features via Heterogenous Graph Embedding Networks. CoRR abs/2008.08617 (2020) - [i3]Haoyan Xu, Ziheng Duan, Yunsheng Bai, Yida Huang, Anni Ren, Qianru Yu, Qianru Zhang, Yueyang Wang, Xiaoqian Wang, Yizhou Sun, Wei Wang:
Multivariate Time Series Classification with Hierarchical Variational Graph Pooling. CoRR abs/2010.05649 (2020)
2010 – 2019
- 2019
- [c17]Kamran Ghasedi, Xiaoqian Wang, Cheng Deng
, Heng Huang:
Balanced Self-Paced Learning for Generative Adversarial Clustering Network. CVPR 2019: 4391-4400 - [i2]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) - [i1]Xiaoqian Wang, Heng Huang:
Approaching Machine Learning Fairness through Adversarial Network. CoRR abs/1909.03013 (2019) - 2018
- [j4]Xiaoqian Wang, Kamran Ghasedi Dizaji, Heng Huang:
Conditional generative adversarial network for gene expression inference. Bioinform. 34(17): i603-i611 (2018) - [j3]Xiaoqian Wang, Hong Chen, Jingwen Yan, Kwangsik Nho, Shannon L. Risacher
, Andrew J. Saykin, Li Shen, Heng Huang:
Quantitative trait loci identification for brain endophenotypes via new additive model with random networks. Bioinform. 34(17): i866-i874 (2018) - [j2]Xiaoqian Wang, Jingwen Yan, Xiaohui Yao, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher
, Andrew J. Saykin, Li Shen, Heng Huang:
Longitudinal Genotype-Phenotype Association Study through Temporal Structure Auto-Learning Predictive Model. J. Comput. Biol. 25(7): 809-824 (2018) - [j1]Xiaoqian Wang, Xiantong Zhen, Quanzheng Li, Dinggang Shen, Heng Huang:
Cognitive Assessment Prediction in Alzheimer's Disease by Multi-Layer Multi-Target Regression. Neuroinformatics 16(3-4): 285-294 (2018) - [c16]Xiaoqian Wang, Hao Huang:
Directional Label Rectification in Adaptive Graph. AAAI 2018: 2548-2555 - [c15]Xiaoqian Wang, Yijun Huang, Ji Liu, Heng Huang:
New Balanced Active Learning Model and Optimization Algorithm. IJCAI 2018: 2826-2832 - [c14]Kamran Ghasedi Dizaji, Xiaoqian Wang, Heng Huang:
Semi-Supervised Generative Adversarial Network for Gene Expression Inference. KDD 2018: 1435-1444 - [c13]Xiaoqian Wang, Weidong Cai
, Dinggang Shen, Heng Huang:
Temporal Correlation Structure Learning for MCI Conversion Prediction. MICCAI (3) 2018: 446-454 - 2017
- [c12]Feiping Nie, Xiaoqian Wang, Heng Huang:
Multiclass Capped ℓp-Norm SVM for Robust Classifications. AAAI 2017: 2415-2421 - [c11]Xiaoqian Wang, Kefei Liu, Jingwen Yan, Shannon L. Risacher
, Andrew J. Saykin
, Li Shen, Heng Huang:
Predicting Interrelated Alzheimer's Disease Outcomes via New Self-learned Structured Low-Rank Model. IPMI 2017: 198-209 - [c10]Hong Chen, Xiaoqian Wang, Cheng Deng, Heng Huang:
Group Sparse Additive Machine. NIPS 2017: 198-208 - [c9]Xiaoqian Wang, Hong Chen, Weidong Cai, Dinggang Shen, Heng Huang:
Regularized Modal Regression with Applications in Cognitive Impairment Prediction. NIPS 2017: 1448-1458 - [c8]Feiping Nie, Xiaoqian Wang, Cheng Deng, Heng Huang:
Learning A Structured Optimal Bipartite Graph for Co-Clustering. NIPS 2017: 4129-4138 - [c7]Xiaoqian Wang, Jingwen Yan, Xiaohui Yao, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher
, Andrew J. Saykin
, Li Shen, Heng Huang:
Longitudinal Genotype-Phenotype Association Study via Temporal Structure Auto-learning Predictive Model. RECOMB 2017: 287-302 - 2016
- [c6]Feiping Nie, Xiaoqian Wang, Michael I. Jordan, Heng Huang:
The Constrained Laplacian Rank Algorithm for Graph-Based Clustering. AAAI 2016: 1969-1976 - [c5]Hongchang Gao, Xiaoqian Wang, Heng Huang:
New Robust Clustering Model for Identifying Cancer Genome Landscapes. ICDM 2016: 151-160 - [c4]Xiaoqian Wang, Feiping Nie
, Heng Huang:
Structured Doubly Stochastic Matrix for Graph Based Clustering: Structured Doubly Stochastic Matrix. KDD 2016: 1245-1254 - [c3]Xiaoqian Wang, Dinggang Shen, Heng Huang:
Prediction of Memory Impairment with MRI Data: A Longitudinal Study of Alzheimer's Disease. MICCAI (1) 2016: 273-281 - 2015
- [c2]Xiaoqian Wang, Yun Liu, Feiping Nie, Heng Huang:
Discriminative Unsupervised Dimensionality Reduction. IJCAI 2015: 3925-3931 - 2014
- [c1]Feiping Nie, Xiaoqian Wang, Heng Huang:
Clustering and projected clustering with adaptive neighbors. KDD 2014: 977-986
Coauthor Index
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last updated on 2024-08-29 20:58 CEST by the dblp team
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