Simon Shaolei Du

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 36

Top Topics

Gradient Method

Markov Decision Process

Reinforcement Learning

Network Congestion

Top Venues

Trans. Mach. Learn. Res.

Publications

Kaifeng Lyu, Jikai Jin, Zhiyuan Li, Simon Shaolei Du, Jason D. Lee, Wei Hu
Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce Grokking. ICLR (2024)
Avinandan Bose, Simon Shaolei Du, Maryam Fazel
Offline Multi-task Transfer RL with Representational Penalization. CoRR (2024)
Haozhe Jiang, Qiwen Cui, Zhihan Xiong, Maryam Fazel, Simon Shaolei Du
A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning. ICLR (2024)
Yifang Chen, Shuohang Wang, Ziyi Yang, Hiteshi Sharma, Nikos Karampatziakis, Donghan Yu, Kevin G. Jamieson, Simon Shaolei Du, Yelong Shen
Cost-Effective Proxy Reward Model Construction with On-Policy and Active Learning. CoRR (2024)
Yiping Wang, Yifang Chen, Wendan Yan, Kevin G. Jamieson, Simon Shaolei Du
Variance Alignment Score: A Simple But Tough-to-Beat Data Selection Method for Multimodal Contrastive Learning. CoRR (2024)
Ruizhe Shi, Yuyao Liu, Yanjie Ze, Simon Shaolei Du, Huazhe Xu
Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning. ICLR (2024)
Zihan Zhang, Jason D. Lee, Yuxin Chen, Simon Shaolei Du
Horizon-Free Regret for Linear Markov Decision Processes. ICLR (2024)
Yiping Wang, Yifang Chen, Wendan Yan, Alex Fang, Wenjing Zhou, Kevin Jamieson, Simon Shaolei Du
CLIPLoss and Norm-Based Data Selection Methods for Multimodal Contrastive Learning. CoRR (2024)
Zhaoyi Zhou, Chuning Zhu, Runlong Zhou, Qiwen Cui, Abhishek Gupta, Simon Shaolei Du
Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning. ICLR (2024)
Nuoya Xiong, Lijun Ding, Simon Shaolei Du
How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing: The Curses of Symmetry and Initialization. ICLR (2024)
Yuandong Tian, Yiping Wang, Zhenyu Zhang, Beidi Chen, Simon Shaolei Du
JoMA: Demystifying Multilayer Transformers via Joint Dynamics of MLP and Attention. ICLR (2024)
Wenqing Zheng, Hao (Frank) Yang, Jiarui Cai, Peihao Wang, Xuan Jiang, Simon Shaolei Du, Yinhai Wang, Zhangyang Wang
Integrating the traffic science with representation learning for city-wide network congestion prediction. Inf. Fusion 99 (2023)
Haozhe Jiang, Qiwen Cui, Zhihan Xiong, Maryam Fazel, Simon Shaolei Du
Offline Congestion Games: How Feedback Type Affects Data Coverage Requirement. ICLR (2023)
Runlong Zhou, Ruosong Wang, Simon Shaolei Du
Horizon-Free and Variance-Dependent Reinforcement Learning for Latent Markov Decision Processes. ICML (2023)
Jifan Zhang, Yifang Chen, Gregory Canal, Stephen Mussmann, Yinglun Zhu, Simon Shaolei Du, Kevin G. Jamieson, Robert D. Nowak
LabelBench: A Comprehensive Framework for Benchmarking Label-Efficient Learning. CoRR (2023)
Rui Yuan, Simon Shaolei Du, Robert M. Gower, Alessandro Lazaric, Lin Xiao
Linear Convergence of Natural Policy Gradient Methods with Log-Linear Policies. ICLR (2023)
Shicong Cen, Yuejie Chi, Simon Shaolei Du, Lin Xiao
Faster Last-iterate Convergence of Policy Optimization in Zero-Sum Markov Games. ICLR (2023)
Zhaoyi Zhou, Chuning Zhu, Runlong Zhou, Qiwen Cui, Abhishek Gupta, Simon Shaolei Du
Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning. CoRR (2023)
Yan Dai, Ruosong Wang, Simon Shaolei Du
Variance-Aware Sparse Linear Bandits. ICLR (2023)
Shusheng Xu, Yancheng Liang, Yunfei Li, Simon Shaolei Du, Yi Wu
Beyond Information Gain: An Empirical Benchmark for Low-Switching-Cost Reinforcement Learning. Trans. Mach. Learn. Res. 2023 (2023)
Haotian Ye, Xiaoyu Chen, Liwei Wang, Simon Shaolei Du
On the Power of Pre-training for Generalization in RL: Provable Benefits and Hardness. ICML (2023)
Jikai Jin, Zhiyuan Li, Kaifeng Lyu, Simon Shaolei Du, Jason D. Lee
Understanding Incremental Learning of Gradient Descent: A Fine-grained Analysis of Matrix Sensing. ICML (2023)
Runlong Zhou, Zihan Zhang, Simon Shaolei Du
Sharp Variance-Dependent Bounds in Reinforcement Learning: Best of Both Worlds in Stochastic and Deterministic Environments. ICML (2023)
Yiping Wang, Yifang Chen, Kevin Jamieson, Simon Shaolei Du
Improved Active Multi-Task Representation Learning via Lasso. ICML (2023)
Runlong Zhou, Zelin He, Yuandong Tian, Yi Wu, Simon Shaolei Du
Understanding Curriculum Learning in Policy Optimization for Online Combinatorial Optimization. Trans. Mach. Learn. Res. 2023 (2023)
Yunchang Yang, Tianhao Wu, Han Zhong, Evrard Garcelon, Matteo Pirotta, Alessandro Lazaric, Liwei Wang, Simon Shaolei Du
A Reduction-Based Framework for Conservative Bandits and Reinforcement Learning. ICLR (2022)
Xiaoxia Wu, Yuege Xie, Simon Shaolei Du, Rachel Ward
AdaLoss: A Computationally-Efficient and Provably Convergent Adaptive Gradient Method. AAAI (2022)
Zhili Feng, Shaobo Han, Simon Shaolei Du
Provable Adaptation across Multiway Domains via Representation Learning. ICLR (2022)
Simon Shaolei Du, Wei Hu, Sham M. Kakade, Jason D. Lee, Qi Lei
Few-Shot Learning via Learning the Representation, Provably. ICLR (2021)
Zhenggang Tang, Chao Yu, Boyuan Chen, Huazhe Xu, Xiaolong Wang, Fei Fang, Simon Shaolei Du, Yu Wang, Yi Wu
Discovering Diverse Multi-Agent Strategic Behavior via Reward Randomization. ICLR (2021)
Keyulu Xu, Mozhi Zhang, Jingling Li, Simon Shaolei Du, Ken-ichi Kawarabayashi, Stefanie Jegelka
How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks. ICLR (2021)
Shusheng Xu, Yancheng Liang, Yunfei Li, Simon Shaolei Du, Yi Wu
A Benchmark for Low-Switching-Cost Reinforcement Learning. CoRR (2021)
Jiaqi Yang, Wei Hu, Jason D. Lee, Simon Shaolei Du
Impact of Representation Learning in Linear Bandits. ICLR (2021)
Yining Wang, Ruosong Wang, Simon Shaolei Du, Akshay Krishnamurthy
Optimism in Reinforcement Learning with Generalized Linear Function Approximation. ICLR (2021)
Simon Shaolei Du, Jayanth Koushik, Aarti Singh, Barnabás Póczos
Transformation Function Based Methods for Model Shift. CoRR (2016)
Maria-Florina Balcan, Simon Shaolei Du, Yining Wang, Adams Wei Yu
An Improved Gap-Dependency Analysis of the Noisy Power Method. COLT (2016)