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Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization


May 31, 2021
Shicong Cen, Yuting Wei, Yuejie Chi


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Policy Mirror Descent for Regularized Reinforcement Learning: A Generalized Framework with Linear Convergence


May 24, 2021
Wenhao Zhan, Shicong Cen, Baihe Huang, Yuxin Chen, Jason D. Lee, Yuejie Chi


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Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting


May 17, 2021
Gen Li, Yuxin Chen, Yuejie Chi, Yuantao Gu, Yuting Wei


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Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Estimation from Incomplete Measurements


Apr 29, 2021
Tian Tong, Cong Ma, Ashley Prater-Bennette, Erin Tripp, Yuejie Chi


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Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis


Mar 16, 2021
Gen Li, Changxiao Cai, Yuxin Chen, Yuantao Gu, Yuting Wei, Yuejie Chi

* v2 added a matching lower bound, and removed the finite-horizon setting for brevity 

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NCH Sleep DataBank: A Large Collection of Real-world Pediatric Sleep Studies


Feb 26, 2021
Harlin Lee, Boyue Li, Shelly DeForte, Mark Splaingard, Yungui Huang, Yuejie Chi, Simon Lin

* Dataset is available at https://sleepdata.org/datasets/nchsdb 

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Softmax Policy Gradient Methods Can Take Exponential Time to Converge


Feb 22, 2021
Gen Li, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen


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Tightening the Dependence on Horizon in the Sample Complexity of Q-Learning


Feb 12, 2021
Gen Li, Changxiao Cai, Yuxin Chen, Yuantao Gu, Yuting Wei, Yuejie Chi


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Beyond Procrustes: Balancing-Free Gradient Descent for Asymmetric Low-Rank Matrix Sensing


Jan 13, 2021
Cong Ma, Yuanxin Li, Yuejie Chi

* To appear on IEEE Trans. on Signal Processing 

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Spectral Methods for Data Science: A Statistical Perspective


Dec 15, 2020
Yuxin Chen, Yuejie Chi, Jianqing Fan, Cong Ma


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Low-Rank Matrix Recovery with Scaled Subgradient Methods: Fast and Robust Convergence Without the Condition Number


Oct 26, 2020
Tian Tong, Cong Ma, Yuejie Chi


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Fast Global Convergence of Natural Policy Gradient Methods with Entropy Regularization


Aug 10, 2020
Shicong Cen, Chen Cheng, Yuxin Chen, Yuting Wei, Yuejie Chi

* V2 adds new proofs and improved results 

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Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model


Jun 17, 2020
Gen Li, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen


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Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction


Jun 04, 2020
Gen Li, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen


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Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent


May 18, 2020
Tian Tong, Cong Ma, Yuejie Chi


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Manifold Gradient Descent Solves Multi-Channel Sparse Blind Deconvolution Provably and Efficiently


Nov 25, 2019
Laixi Shi, Yuejie Chi

* submitted 

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Subspace Estimation from Unbalanced and Incomplete Data Matrices: $\ell_{2,\infty}$ Statistical Guarantees


Oct 09, 2019
Changxiao Cai, Gen Li, Yuejie Chi, H. Vincent Poor, Yuxin Chen


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Communication-Efficient Distributed Optimization in Networks with Gradient Tracking


Sep 12, 2019
Boyue Li, Shicong Cen, Yuxin Chen, Yuejie Chi


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Vector-Valued Graph Trend Filtering with Non-Convex Penalties


May 29, 2019
Rohan Varma, Harlin Lee, Jelena Kovačević, Yuejie Chi

* The first two authors contributed equally. This paper has been submitted to the IEEE Transactions on Signal and Information Processing over Networks. A preliminary version of partial results in this paper was presented at 2019 IEEE ICASSP 

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Convergence of Distributed Stochastic Variance Reduced Methods without Sampling Extra Data


May 29, 2019
Shicong Cen, Huishuai Zhang, Yuejie Chi, Wei Chen, Tie-Yan Liu


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Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization


Feb 20, 2019
Yuxin Chen, Yuejie Chi, Jianqing Fan, Cong Ma, Yuling Yan


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Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview


Sep 25, 2018
Yuejie Chi, Yue M. Lu, Yuxin Chen


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Streaming PCA and Subspace Tracking: The Missing Data Case


Jun 12, 2018
Laura Balzano, Yuejie Chi, Yue M. Lu

* 27 pages, 7 figures, submitted to the Proceedings of IEEE 

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Harnessing Structures in Big Data via Guaranteed Low-Rank Matrix Estimation


May 02, 2018
Yudong Chen, Yuejie Chi

* To appear in IEEE Signal Processing Magazine 

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Gradient Descent with Random Initialization: Fast Global Convergence for Nonconvex Phase Retrieval


Mar 21, 2018
Yuxin Chen, Yuejie Chi, Jianqing Fan, Cong Ma


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Local Geometry of One-Hidden-Layer Neural Networks for Logistic Regression


Feb 18, 2018
Haoyu Fu, Yuejie Chi, Yingbin Liang


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Nonconvex Matrix Factorization from Rank-One Measurements


Feb 17, 2018
Yuanxin Li, Cong Ma, Yuxin Chen, Yuejie Chi

* 33 pages 

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