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Du, Simon S.

  1. Gradient Descent Finds Global Minima of Deep Neural Networks
    2018/11/09 by Simon S. Du, Du, Simon S., Jason D. Lee +7 · 1 voice · 44 citations
    Engineering · Computer Science · #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques #Machine Learning and ELM
  2. Fine-Grained Analysis of Optimization and Generalization for\n Overparameterized Two-Layer Neural Networks
    2019/01/24 by Sanjeev Arora, Simon S. Du, Arora, Sanjeev +7 · 71 citations
    Computer Science · #Advanced Neural Network Applications #Stochastic Gradient Optimization Techniques #Machine Learning and ELM
  3. Gradient Descent Provably Optimizes Over-parameterized Neural Networks
    2018/10/04 by Du, Simon S., Zhai, Xiyu, Poczos, Barnabas +1 · 34 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  4. On Exact Computation with an Infinitely Wide Neural Net
    2019/04/26 by Sanjeev Arora, Simon S. Du, Arora, Sanjeev +9 · 32 citations
    Computer Science · #Gaussian Processes and Bayesian Inference #Stochastic Gradient Optimization Techniques #Advanced Neural Network Applications
  5. Understanding the Acceleration Phenomenon via High-Resolution Differential Equations
    2018/10/21 by Shi, Bin, Du, Simon S., Jordan, Michael I. +1 · 20 citations
    #Classical Analysis and ODEs (math.CA) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Numerical Analysis (math.NA) #Optimization and Control (math.OC)
  6. Algorithmic Regularization in Learning Deep Homogeneous Models: Layers\n are Automatically Balanced
    2018/06/03 by Simon S. Du, Wei Hu, Du, Simon S. +3 · 15 citations
    Computer Science · Engineering · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Matrix Theory and Algorithms #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
  7. How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks
    2020/09/24 by Keyulu Xu, Mozhi Zhang, Xu, Keyulu +9 · 18 citations
    Computer Science · #Domain Adaptation and Few-Shot Learning #Stochastic Gradient Optimization Techniques #Machine Learning and ELM
  8. Provably efficient RL with Rich Observations via Latent State Decoding
    2019/01/25 by Simon S. Du, Du, Simon S., Akshay Krishnamurthy +9 · 15 citations
    Computer Science · #Machine Learning and Algorithms #Data Stream Mining Techniques #Adversarial Robustness in Machine Learning
  9. Few-Shot Learning via Learning the Representation, Provably
    2020/02/21 by Simon S. Du, Du, Simon S., Wei Hu +7 · 21 citations
    Computer Science · Engineering · #Domain Adaptation and Few-Shot Learning #Machine Learning and ELM #Sparse and Compressive Sensing Techniques
  10. What Can Neural Networks Reason About?
    2019/05/30 by Xu, Keyulu, Li, Jingling, Zhang, Mozhi +3 · 7 citations
    #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural and Evolutionary Computing (cs.NE)
  11. Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels
    2019/05/30 by Simon S. Du, Du, Simon S., Kangcheng Hou +9 · 6 citations
    Computer Science · #Advanced Graph Neural Networks #Advanced Neural Network Applications #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Topic Modeling
  12. Is a Good Representation Sufficient for Sample Efficient Reinforcement\n Learning?
    2019/10/07 by Simon S. Du, Du, Simon S., Sham M. Kakade +5 · 8 citations
    Computer Science · Decision Sciences · #Adaptive Dynamic Programming Control #Advanced Bandit Algorithms Research #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Optimization and Control (math.OC) #Reinforcement Learning in Robotics
  13. Decoding-Time Language Model Alignment with Multiple Objectives
    2024/06/27 by Shi, Ruizhe, Chen, Yifang, Hu, Yushi +4 · 13 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
  14. Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce Grokking
    2023/11/30 by Lyu, Kaifeng, Jin, Jikai, Li, Zhiyuan +3 · 10 citations
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  15. Global Convergence of Gradient Descent for Asymmetric Low-Rank Matrix Factorization
    2021/06/27 by Ye Tian, Ye, Tian, Simon S. Du +1 · 6 citations
    Engineering · #Sparse and Compressive Sensing Techniques #Antenna Design and Optimization #Advanced Adaptive Filtering Techniques
  16. Denoised MDPs: Learning World Models Better Than the World Itself
    2022/06/30 by Tongzhou Wang, Wang, Tongzhou, Simon S. Du +9 · 1 voice · 5 citations
    #cs.LG
  17. Fine-Grained Gap-Dependent Bounds for Tabular MDPs via Adaptive Multi-Step Bootstrap
    2021/02/09 by Haike Xu, Tengyu Ma, Xu, Haike +3 · 7 citations
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Reinforcement Learning in Robotics
  18. Gradient Descent Can Take Exponential Time to Escape Saddle Points
    2017/05/29 by Du, Simon S., Jin, Chi, Lee, Jason D. +3 · 4 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  19. When is a Convolutional Filter Easy To Learn?
    2017/09/18 by Simon S. Du, Du, Simon S., Jason D. Lee +3 · 11 citations
    Computer Science · #Neural Networks and Applications #Anomaly Detection Techniques and Applications #Speech and Audio Processing
  20. Q-learning with Logarithmic Regret
    2020/06/16 by Kunhe Yang, Lin F. Yang, Yang, Kunhe +3 · 4 citations
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Optimization and Control (math.OC) #Reinforcement Learning in Robotics
  21. Improved Variance-Aware Confidence Sets for Linear Bandits and Linear\n Mixture MDP
    2021/01/29 by Zihan Zhang, Jiaqi Yang, Zhang, Zihan +5 · 4 citations
    Decision Sciences · Computer Science · #Advanced Bandit Algorithms Research #Reinforcement Learning in Robotics #Machine Learning and Algorithms
  22. An Improved Gap-Dependency Analysis of the Noisy Power Method
    2016/02/23 by Balcan, Maria Florina, Du, Simon S., Wang, Yining +1 · 3 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Numerical Analysis (math.NA)
  23. Settling the Sample Complexity of Online Reinforcement Learning
    2023/07/25 by Zhang, Zihan, Chen, Yuxin, Lee, Jason D. +1 · 1 voice · 5 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
  24. Bilinear Classes: A Structural Framework for Provable Generalization in RL
    2021/03/19 by Du, Simon S., Kakade, Sham M., Lee, Jason D. +4 · 4 citations
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  25. Stochastic Variance Reduction Methods for Policy Evaluation
    2017/02/25 by Du, Simon S., Chen, Jianshu, Li, Lihong +2 · 3 citations
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Systems and Control (eess.SY) #electronic engineering #information engineering
  26. Understanding Incremental Learning of Gradient Descent: A Fine-grained Analysis of Matrix Sensing
    2023/01/27 by Jin, Jikai, Li, Zhiyuan, Lyu, Kaifeng +2 · 5 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  27. Reward-Free RL is No Harder Than Reward-Aware RL in Linear Markov Decision Processes
    2022/01/26 by Wagenmaker, Andrew, Chen, Yifang, Simchowitz, Max +2 · 4 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  28. First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach
    2021/12/07 by Andrew Wagenmaker, Wagenmaker, Andrew, Yifang Chen +7 · 4 citations
    Computer Science · Decision Sciences · Engineering · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Reinforcement Learning in Robotics #Smart Grid Energy Management
  29. Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks
    2019/10/03 by Arora, Sanjeev, Du, Simon S., Li, Zhiyuan +3 · 3 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  30. Learning to Cooperate with Humans using Generative Agents
    2024/11/21 by Yancheng Liang, Daphne Chen, Liang, Yancheng +7 · 1 voice · 6 citations
    Computer Science · #Multi-Agent Systems and Negotiation #cs.AI #cs.LG #cs.MA
  31. Sharp Variance-Dependent Bounds in Reinforcement Learning: Best of Both Worlds in Stochastic and Deterministic Environments
    2023/01/31 by Zhou, Runlong, Zhang, Zihan, Du, Simon S. · 4 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  32. Impact of Representation Learning in Linear Bandits
    2020/10/13 by Jiaqi Yang, Wei Hu, Yang, Jiaqi +5 · 3 citations
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Algorithms #Reinforcement Learning in Robotics
  33. DualSMC: Tunneling Differentiable Filtering and Planning under Continuous POMDPs
    2019/09/28 by Yunbo Wang, Wang, Yunbo, Bo Liu +11 · 4 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Advanced Neural Network Applications #Domain Adaptation and Few-Shot Learning
  34. Active Multi-Task Representation Learning
    2022/02/02 by Chen, Yifang, Du, Simon S., Jamieson, Kevin · 3 citations
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  35. How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing: The Curses of Symmetry and Initialization
    2023/10/03 by Nuoya Xiong, Lijun Ding, Xiong, Nuoya +3 · 4 citations
    Engineering · Computer Science · Physics and Astronomy · #Sparse and Compressive Sensing Techniques #Quantum Information and Cryptography #Orbital Angular Momentum in Optics
  36. Cross-environment Cooperation Enables Zero-shot Multi-agent Coordination
    2025/04/17 by Kunal Jha, Wilka Carvalho, Jha, Kunal +9 · 1 voice · 9 citations
    Computer Science · Psychology · #cs.MA #cs.AI #cs.LG
  37. Faster Last-iterate Convergence of Policy Optimization in Zero-Sum Markov Games
    2022/10/03 by Shicong Cen, Cen, Shicong, Yuejie Chi +5 · 3 citations
    Computer Science · Decision Sciences · Engineering · #Reinforcement Learning in Robotics #Advanced Bandit Algorithms Research #Smart Grid Energy Management
  38. Is Reinforcement Learning More Difficult Than Bandits? A Near-optimal\n Algorithm Escaping the Curse of Horizon
    2020/09/28 by Zihan Zhang, Zhang, Zihan, Xiangyang Ji +3 · 4 citations
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Data Stream Mining Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Reinforcement Learning in Robotics
  39. Optimism in Reinforcement Learning with Generalized Linear Function Approximation
    2019/12/09 by Wang, Yining, Wang, Ruosong, Du, Simon S. +1 · 2 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  40. Enhanced Convolutional Neural Tangent Kernels
    2019/11/03 by Li, Zhiyuan, Wang, Ruosong, Yu, Dingli +4 · 2 citations
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural and Evolutionary Computing (cs.NE)
  41. A Provably Efficient Algorithm for Linear Markov Decision Process with Low Switching Cost
    2021/01/02 by Minbo Gao, Gao, Minbo, Tianle Xie +5 · 3 citations
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Age of Information Optimization #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Reinforcement Learning in Robotics
  42. Provable Representation Learning for Imitation Learning via Bi-level Optimization
    2020/02/24 by Sanjeev Arora, Simon S. Du, Arora, Sanjeev +7 · 2 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Artificial Intelligence (cs.AI) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Reinforcement Learning in Robotics
  43. An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models
    2024/01/12 by Gantavya Bhatt, Yifang Chen, Bhatt, Gantavya +21 · 4 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Algorithms #Natural Language Processing Techniques #Topic Modeling
  44. Stochastic Shortest Path: Minimax, Parameter-Free and Towards Horizon-Free Regret
    2021/04/22 by Tarbouriech, Jean, Zhou, Runlong, Du, Simon S. +3 · 2 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
  45. Anytime Acceleration of Gradient Descent
    2024/11/26 by Zihan Zhang, Zhang, Zihan, Jason D. Lee +5 · 3 voices · 2 citations
    Engineering · #Welding Techniques and Residual Stresses #cs.LG #eess.SY #math.OC #stat.ML
  46. Provably Efficient Offline Multi-agent Reinforcement Learning via Strategy-wise Bonus
    2022/06/01 by Qiwen Cui, Simon S. Du, Cui, Qiwen +1 · 2 citations
    Computer Science · Decision Sciences · #Artificial Intelligence (cs.AI) #Auction Theory and Applications #Computer Science and Game Theory (cs.GT) #FOS: Computer and information sciences #Game Theory and Applications #Machine Learning (cs.LG) #Multiagent Systems (cs.MA) #Reinforcement Learning in Robotics
  47. Linear Convergence of Natural Policy Gradient Methods with Log-Linear Policies
    2022/10/04 by Rui Yuan, Yuan, Rui, Simon S. Du +7 · 2 citations
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Optimization and Control (math.OC) #Reinforcement Learning in Robotics #Stochastic Gradient Optimization Techniques
  48. Rethinking Transformers in Solving POMDPs
    2024/05/27 by Lu, Chenhao, Shi, Ruizhe, Liu, Yuyao +3 · 3 citations
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  49. Breaking the Curse of Multiagents in a Large State Space: RL in Markov Games with Independent Linear Function Approximation
    2023/02/07 by Cui, Qiwen, Zhang, Kaiqing, Du, Simon S. · 2 citations
    #Artificial Intelligence (cs.AI) #Computer Science and Game Theory (cs.GT) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Multiagent Systems (cs.MA)
  50. Preference-Based Multi-Agent Reinforcement Learning: Data Coverage and Algorithmic Techniques
    2024/09/01 by Zhang, Natalia, Wang, Xinqi, Cui, Qiwen +3 · 3 citations
    #Artificial Intelligence (cs.AI) #Computer Science and Game Theory (cs.GT) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Multiagent Systems (cs.MA)
  51. Global Convergence of Adaptive Gradient Methods for An Over-parameterized Neural Network
    2019/02/19 by Xiaoxia Wu, Wu, Xiaoxia, Simon S. Du +3 · 2 citations
    Computer Science · Engineering · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and ELM #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
  52. Linear Convergence of the Primal-Dual Gradient Method for Convex-Concave Saddle Point Problems without Strong Convexity
    2018/02/05 by Du, Simon S., Hu, Wei · 1 citation
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  53. How Many Samples are Needed to Estimate a Convolutional or Recurrent Neural Network?
    2018/05/21 by Du, Simon S., Wang, Yining, Zhai, Xiyu +3 · 1 citation
    #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  54. On the Power of Over-parametrization in Neural Networks with Quadratic Activation
    2018/03/03 by Simon S. Du, Du, Simon S., Jason D. Lee +1 · 1 citation
    Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Optimization and Control (math.OC)
  55. Robust Nonparametric Regression under Huber's ε-contamination Model
    2018/05/26 by Du, Simon S., Wang, Yining, Balakrishnan, Sivaraman +2 · 1 citation
    #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Statistics Theory (math.ST)
  56. Towards Understanding the Importance of Shortcut Connections in Residual Networks
    2019/09/10 by Liu, Tianyi, Chen, Minshuo, Zhou, Mo +3 · 1 citation
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  57. Acceleration via Symplectic Discretization of High-Resolution Differential Equations
    2019/02/11 by Bin Shi, Simon S. Du, Shi, Bin +5 · 1 citation
    Computer Science · Economics, Econometrics and Finance · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Matrix Theory and Algorithms #Numerical Analysis (math.NA) #Optimization and Control (math.OC) #Stochastic Gradient Optimization Techniques #Stochastic processes and financial applications
  58. Agnostic Q-learning with Function Approximation in Deterministic Systems: Tight Bounds on Approximation Error and Sample Complexity
    2020/02/17 by Du, Simon S., Lee, Jason D., Mahajan, Gaurav +1 · 1 citation
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  59. Over-parameterized Adversarial Training: An Analysis Overcoming the Curse of Dimensionality
    2020/02/16 by Zhang, Yi, Plevrakis, Orestis, Du, Simon S. +3 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  60. Reflect-RL: Two-Player Online RL Fine-Tuning for LMs
    2024/02/20 by Runlong Zhou, Zhou, Runlong, Simon S. Du +3 · 2 citations
    Engineering · #Computation and Language (cs.CL) #Experimental Learning in Engineering #FOS: Computer and information sciences #Machine Learning (cs.LG)
  61. On Reward-Free Reinforcement Learning with Linear Function Approximation
    2020/06/19 by Wang, Ruosong, Du, Simon S., Yang, Lin F. +1 · 1 citation
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  62. On the Power of Multitask Representation Learning in Linear MDP
    2021/06/15 by Lu, Rui, Huang, Gao, Du, Simon S. · 1 citation
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  63. Improved Learning of One-hidden-layer Convolutional Neural Networks with Overlaps
    2018/05/20 by Simon S. Du, Du, Simon S., Surbhi Goel +1 · 2 citations
    Computer Science · Engineering · #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
  64. Improved Corruption Robust Algorithms for Episodic Reinforcement\n Learning
    2021/02/13 by Yifang Chen, Simon S. Du, Chen, Yifang +3 · 1 citation
    Computer Science · Decision Sciences · Engineering · #Advanced Bandit Algorithms Research #Artificial Intelligence (cs.AI) #Auction Theory and Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Reinforcement Learning in Robotics #Smart Grid Energy Management
  65. Nearly Horizon-Free Offline Reinforcement Learning
    2021/03/25 by Ren, Tongzheng, Li, Jialian, Dai, Bo +2 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  66. Towards Demystifying Representation Learning with Non-contrastive Self-supervision
    2021/10/11 by Wang, Xiang, Chen, Xinlei, Du, Simon S. +1 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  67. On the Power of Pre-training for Generalization in RL: Provable Benefits and Hardness
    2022/10/19 by Ye, Haotian, Chen, Xiaoyu, Wang, Liwei +1 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
  68. Nearly Optimal Policy Optimization with Stable at Any Time Guarantee
    2021/12/21 by Tianhao Wu, Yunchang Yang, Wu, Tianhao +9 · 1 citation
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Reinforcement Learning in Robotics
  69. Nearly Minimax Algorithms for Linear Bandits with Shared Representation
    2022/03/29 by Jiaqi Yang, Lei Qi, Yang, Jiaqi +5 · 1 citation
    Decision Sciences · Computer Science · #Advanced Bandit Algorithms Research #Optimization and Search Problems #Age of Information Optimization
  70. Learning in Congestion Games with Bandit Feedback
    2022/06/04 by Qiwen Cui, Zhihan Xiong, Cui, Qiwen +5 · 1 citation
    Decision Sciences · #Advanced Bandit Algorithms Research #Auction Theory and Applications #Computer Science and Game Theory (cs.GT) #FOS: Computer and information sciences #Game Theory and Applications #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Multiagent Systems (cs.MA)
  71. Horizon-Free Reinforcement Learning in Polynomial Time: the Power of Stationary Policies
    2022/03/24 by Zhang, Zihan, Ji, Xiangyang, Du, Simon S. · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
  72. On Gap-dependent Bounds for Offline Reinforcement Learning
    2022/06/01 by Xinqi Wang, Qiwen Cui, Wang, Xinqi +3 · 1 citation
    Computer Science · #Adversarial Robustness in Machine Learning #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Algorithms #Reinforcement Learning in Robotics
  73. Optimal Extragradient-Based Bilinearly-Coupled Saddle-Point Optimization
    2022/06/17 by Du, Simon S., Gidel, Gauthier, Jordan, Michael I. +1 · 1 citation
    #Computational Complexity (cs.CC) #Computer Science and Game Theory (cs.GT) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Optimization and Control (math.OC)
  74. The Crucial Role of Samplers in Online Direct Preference Optimization
    2024/09/29 by Shi, Ruizhe, Zhou, Runlong, Du, Simon S. · 2 citations
    #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  75. Horizon-Free and Variance-Dependent Reinforcement Learning for Latent Markov Decision Processes
    2022/10/20 by Zhou, Runlong, Wang, Ruosong, Du, Simon S. · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
  76. Improved Active Multi-Task Representation Learning via Lasso
    2023/06/05 by Yiping Wang, Wang, Yiping, Yifang Chen +5 · 1 citation
    Computer Science · Engineering · Decision Sciences · #Domain Adaptation and Few-Shot Learning #Sparse and Compressive Sensing Techniques #Advanced Bandit Algorithms Research
  77. A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning
    2023/06/12 by Jiang, Haozhe, Cui, Qiwen, Xiong, Zhihan +2 · 1 citation
    #Artificial Intelligence (cs.AI) #Computer Science and Game Theory (cs.GT) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Multiagent Systems (cs.MA)
  78. Toward Global Convergence of Gradient EM for Over-Parameterized Gaussian Mixture Models
    2024/06/29 by Weihang Xu, Xu, Weihang, Maryam Fazel +3 · 2 citations
    Computer Science · #Algorithms and Data Compression #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  79. Optimal Multi-Distribution Learning
    2023/12/08 by Zhang, Zihan, Zhan, Wenhao, Chen, Yuxin +2 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  80. Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning
    2023/10/31 by Shi, Ruizhe, Liu, Yuyao, Ze, Yanjie +2 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
  81. Extragradient Preference Optimization (EGPO): Beyond Last-Iterate Convergence for Nash Learning from Human Feedback
    2025/03/11 by Zhou, Runlong, Fazel, Maryam, Du, Simon S. · 2 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
  82. Width Provably Matters in Optimization for Deep Linear Neural Networks
    2019/01/24 by Simon S. Du, Wei Hu, Du, Simon S. +1 · 2 citations
    Computer Science · #Advanced Neural Network Applications #FOS: Computer and information sciences #Face and Expression Recognition #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Stochastic Gradient Optimization Techniques
  83. Understanding the Gains from Repeated Self-Distillation
    2024/07/05 by Divyansh Pareek, Pareek, Divyansh, Simon S. Du +3 · 2 citations
    Engineering · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Process Optimization and Integration
  84. Improving Human-AI Coordination through Online Adversarial Training and Generative Models
    2025/04/21 by Paresh Chaudhary, Yancheng Liang, Chaudhary, Paresh +7 · 2 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences
  85. Distributional Successor Features Enable Zero-Shot Policy Optimization
    2024/03/10 by Zhu, Chuning, Wang, Xinqi, Han, Tyler +2 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
  86. Understanding the Performance Gap in Preference Learning: A Dichotomy of RLHF and DPO
    2025/05/26 by Ruizhe Shi, Shi, Ruizhe, Runlong Zhou +8 · 2 citations
    Decision Sciences · Computer Science · #Multi-Criteria Decision Making #Semantic Web and Ontologies