Wang, Shusen

27 publications

MLJ 2024 Fedpower: Privacy-Preserving Distributed Eigenspace Estimation Xiao Guo, Xiang Li, Xiangyu Chang, Shusen Wang, Zhihua Zhang

AAAI 2024 Xiezhi: An Ever-Updating Benchmark for Holistic Domain Knowledge Evaluation Zhouhong Gu, Xiaoxuan Zhu, Haoning Ye, Lin Zhang, Jianchen Wang, Yixin Zhu, Sihang Jiang, Zhuozhi Xiong, Zihan Li, Weijie Wu, Qianyu He, Rui Xu, Wenhao Huang, Jingping Liu, Zili Wang, Shusen Wang, Weiguo Zheng, Hongwei Feng, Yanghua Xiao

AISTATS 2022 Federated Reinforcement Learning with Environment Heterogeneity Hao Jin, Yang Peng, Wenhao Yang, Shusen Wang, Zhihua Zhang

IJCAI 2022 Learning by Interpreting Xuting Tang, Abdul Rafae Khan, Shusen Wang, Jia Xu

ICML 2021 Communication-Efficient Distributed SVD via Local Power Iterations Xiang Li, Shusen Wang, Kun Chen, Zhihua Zhang

ICML 2021 Matrix Sketching for Secure Collaborative Machine Learning Mengjiao Zhang, Shusen Wang

AAAI 2020 Do Subsampled Newton Methods Work for High-Dimensional Data? Xiang Li, Shusen Wang, Zhihua Zhang

ICLR 2020 On the Convergence of FedAvg on Non-IID Data Xiang Li, Kaixuan Huang, Wenhao Yang, Shusen Wang, Zhihua Zhang

JMLR 2019 A Bootstrap Method for Error Estimation in Randomized Matrix Multiplication Miles E. Lopes, Shusen Wang, Michael W. Mahoney

AAAI 2019 A Sharper Generalization Bound for Divide-and-Conquer Ridge Regression Shusen Wang

JMLR 2019 Scalable Kernel K-Means Clustering with Nystrom Approximation: Relative-Error Bounds Shusen Wang, Alex Gittens, Michael W. Mahoney

ICML 2018 Error Estimation for Randomized Least-Squares Algorithms via the Bootstrap Miles Lopes, Shusen Wang, Michael Mahoney

NeurIPS 2018 GIANT: Globally Improved Approximate Newton Method for Distributed Optimization Shusen Wang, Fred Roosta, Peng Xu, Michael W. Mahoney

ICML 2017 Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging Shusen Wang, Alex Gittens, Michael W. Mahoney

JMLR 2016 SPSD Matrix Approximation Vis Column Selection: Theories, Algorithms, and Extensions Shusen Wang, Luo Luo, Zhihua Zhang

JMLR 2016 Towards More Efficient SPSD Matrix Approximation and CUR Matrix Decomposition Shusen Wang, Zhihua Zhang, Tong Zhang

IJCAI 2015 Open Domain Short Text Conceptualization: A Generative + Descriptive Modeling Approach Yangqiu Song, Shusen Wang, Haixun Wang

AISTATS 2014 Efficient Algorithms and Error Analysis for the Modified Nystrom Method Shusen Wang, Zhihua Zhang

AAAI 2014 Exact Subspace Clustering in Linear Time Shusen Wang, Bojun Tu, Congfu Xu, Zhihua Zhang

ICML 2014 Making Fisher Discriminant Analysis Scalable Bojun Tu, Zhihua Zhang, Shusen Wang, Hui Qian

AAAI 2014 Using the Matrix Ridge Approximation to Speedup Determinantal Point Processes Sampling Algorithms Shusen Wang, Chao Zhang, Hui Qian, Zhihua Zhang

JMLR 2013 Improving CUR Matrix Decomposition and the Nystrom Approximation via Adaptive Sampling Shusen Wang, Zhihua Zhang

IJCAI 2013 Nonconvex Relaxation Approaches to Robust Matrix Recovery Shusen Wang, Dehua Liu, Zhihua Zhang

NeurIPS 2012 A Scalable CUR Matrix Decomposition Algorithm: Lower Time Complexity and Tighter Bound Shusen Wang, Zhihua Zhang

AAAI 2012 Colorization by Matrix Completion Shusen Wang, Zhihua Zhang

JMLR 2012 EP-GIG Priors and Applications in Bayesian Sparse Learning Zhihua Zhang, Shusen Wang, Dehua Liu, Michael I. Jordan

AAAI 2011 Efficient Subspace Segmentation via Quadratic Programming Shusen Wang, Xiaotong Yuan, Tiansheng Yao, Shuicheng Yan, Jialie Shen