Shangtong Zhang

85 papers A* 24A 3B 1Journal 54Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Almost Sure Convergence of Differential Temporal Difference Learning for Average Reward Markov Decision Processes. CoRR Ethan Blaser, Jiuqi Wang, Shangtong Zhang
2026	A*	`conf`	Asymptotic and Finite Sample Analysis of Nonexpansive Stochastic Approximations with Markovian Noise. AAAI Ethan Blaser, Shangtong Zhang
2026	J	`jnl`	MathlibLemma: Folklore Lemma Generation and Benchmark for Formal Mathematics. CoRR Xinyu Liu, Zixuan Xie, Amir Moeini, Claire Chen, Shuze Daniel Liu, Yu Meng, Aidong Zhang, Shangtong Zhang
2026	J	`jnl`	Multi-agent DRL-based Lane Change Decision Model for Cooperative Planning in Mixed Traffic. CoRR Zeyu Mu, Shangtong Zhang, B. Brian Park
2025	J	`jnl`	A Survey of In-Context Reinforcement Learning. CoRR Amir Moeini, Jiuqi Wang, Jacob Beck, Ethan Blaser, Shimon Whiteson, Rohan Chandra, Shangtong Zhang
2025	A*	`conf`	Counterfactual Explanations for Continuous Action Reinforcement Learning. IJCAI Shuyang Dong, Shangtong Zhang, Lu Feng
2025	J	`jnl`	Counterfactual Explanations for Continuous Action Reinforcement Learning. CoRR Shuyang Dong, Shangtong Zhang, Lu Feng
2025	A*	`conf`	Doubly Optimal Policy Evaluation for Reinforcement Learning. ICLR Shuze Daniel Liu, Claire Chen, Shangtong Zhang
2025	A*	`conf`	Efficient Multi-Policy Evaluation for Reinforcement Learning. AAAI Shuze Daniel Liu, Claire Chen, Shangtong Zhang
2025	A*	`conf`	Efficient Policy Evaluation with Safety Constraint for Reinforcement Learning. ICLR Claire Chen, Shuze Daniel Liu, Shangtong Zhang
2025	J	`jnl`	Experience Replay Addresses Loss of Plasticity in Continual Learning. CoRR Jiuqi Wang, Rohan Chandra, Shangtong Zhang
2025	J	`jnl`	Extensions of Robbins-Siegmund Theorem with Applications in Reinforcement Learning. CoRR Xinyu Liu, Zixuan Xie, Shangtong Zhang
2025	J	`jnl`	Finite Sample Analysis of Linear Temporal Difference Learning with Arbitrary Features. CoRR Zixuan Xie, Xinyu Liu, Rohan Chandra, Shangtong Zhang
2025	—	`conf`	GameChat: Multi-LLM Dialogue for Safe, Agile, and Socially Optimal Multi-Agent Navigation in Constrained Environments. MRS Vagul Mahadevan, Shangtong Zhang, Rohan Chandra
2025	J	`jnl`	GameChat: Multi-LLM Dialogue for Safe, Agile, and Socially Optimal Multi-Agent Navigation in Constrained Environments. CoRR Vagul Mahadevan, Shangtong Zhang, Rohan Chandra
2025	J	`jnl`	Group Fairness in Multi-Task Reinforcement Learning. CoRR Kefan Song, Runnan Jiang, Rohan Chandra, Shangtong Zhang
2025	J	`jnl`	Linear CoRR Xinyu Liu, Zixuan Xie, Shangtong Zhang
2025	A*	`conf`	Linear Q-Learning Does Not Diverge in L2: Convergence Rates to a Bounded Set. ICML Xinyu Liu, Zixuan Xie, Shangtong Zhang
2025	J	`jnl`	Prompt-Driven Domain Adaptation for End-to-End Autonomous Driving via In-Context RL. CoRR Aleesha Khurram, Amir Moeini, Shangtong Zhang, Rohan Chandra
2025	A*	`conf`	Revisiting a Design Choice in Gradient Temporal Difference Learning. ICLR Xiaochi Qian, Shangtong Zhang
2025	J	`jnl`	Reward Is Enough: LLMs Are In-Context Reinforcement Learners. CoRR Kefan Song, Amir Moeini, Peng Wang, Lei Gong, Rohan Chandra, Yanjun Qi, Shangtong Zhang
2025	J	`jnl`	Safe In-Context Reinforcement Learning. CoRR Amir Moeini, Minjae Kwon, Alper Kamil Bozkurt, Yuichi Motai, Rohan Chandra, Lu Feng, Shangtong Zhang
2025	J	`jnl`	The ODE Method for Stochastic Approximation and Reinforcement Learning with Markovian Noise. J. Mach. Learn. Res. Shuze Daniel Liu, Shuhang Chen, Shangtong Zhang
2025	J	`jnl`	Towards Formalizing Reinforcement Learning Theory. CoRR Shangtong Zhang
2025	J	`jnl`	Towards Large Language Models that Benefit for All: Benchmarking Group Fairness in Reward Models. CoRR Kefan Song, Jin Yao, Runnan Jiang, Rohan Chandra, Shangtong Zhang
2025	J	`jnl`	Towards Provable Emergence of In-Context Reinforcement Learning. CoRR Jiuqi Wang, Rohan Chandra, Shangtong Zhang
2025	A*	`conf`	Transformers Can Learn Temporal Difference Methods for In-Context Reinforcement Learning. ICLR Jiuqi Wang, Ethan Blaser, Hadi Daneshmand, Shangtong Zhang
2024	J	`jnl`	Almost Sure Convergence Rates and Concentration of Stochastic Approximation and Reinforcement Learning with Markovian Noise. CoRR Xiaochi Qian, Zixuan Xie, Xinyu Liu, Shangtong Zhang
2024	J	`jnl`	Almost Sure Convergence of Average Reward Temporal Difference Learning. CoRR Ethan Blaser, Shangtong Zhang
2024	J	`jnl`	Almost Sure Convergence of Linear Temporal Difference Learning with Arbitrary Features. CoRR Jiuqi Wang, Shangtong Zhang
2024	J	`jnl`	CRASH: Challenging Reinforcement-Learning Based Adversarial Scenarios For Safety Hardening. CoRR Amar Kulkarni, Shangtong Zhang, Madhur Behl
2024	—	`conf`	CRISP: Triangle Counting Acceleration via Content Addressable Memory-Integrated 3D-Stacked Memory. ITC-Asia Shangtong Zhang, Xueyan Wang, Weisheng Zhao, Yier Jin
2024	J	`jnl`	Doubly Optimal Policy Evaluation for Reinforcement Learning. CoRR Shuze Daniel Liu, Claire Chen, Shangtong Zhang
2024	J	`jnl`	Efficient Multi-Policy Evaluation for Reinforcement Learning. CoRR Shuze Daniel Liu, Yuxin Chen, Shangtong Zhang
2024	A*	`conf`	Efficient Policy Evaluation with Offline Data Informed Behavior Policy Design. ICML Shuze Daniel Liu, Shangtong Zhang
2024	J	`jnl`	Efficient Policy Evaluation with Safety Constraint for Reinforcement Learning. CoRR Claire Chen, Shuze Daniel Liu, Shangtong Zhang
2024	J	`jnl`	The ODE Method for Stochastic Approximation and Reinforcement Learning with Markovian Noise. CoRR Shuze Daniel Liu, Shuhang Chen, Shangtong Zhang
2024	J	`jnl`	Transformers Learn Temporal Difference Methods for In-Context Reinforcement Learning. CoRR Jiuqi Wang, Ethan Blaser, Hadi Daneshmand, Shangtong Zhang
2023	A*	`conf`	A New Challenge in Policy Evaluation. AAAI Shangtong Zhang
2023	J	`jnl`	AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning. CoRR Michaël Mathieu, Sherjil Ozair, Srivatsan Srinivasan, Çaglar Gülçehre, Shangtong Zhang, Ray Jiang, Tom Le Paine, Richard Powell, Konrad Zolna, Julian Schrittwieser, David H. Choi, Petko Georgiev, Daniel Toyama, Aja Huang, Roman Ring, Igor Babuschkin, Timo Ewalds, Mahyar Bordbar, Sarah Henderson, Sergio Gómez Colmenarejo, Aäron van den Oord, Wojciech Marian Czarnecki, Nando de Freitas, Oriol Vinyals
2023	J	`jnl`	Direct Gradient Temporal Difference Learning. CoRR Xiaochi Qian, Shangtong Zhang
2023	J	`jnl`	IMGA: Efficient In-Memory Graph Convolution Network Aggregation With Data Flow Optimizations. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Yuntao Wei, Xueyan Wang, Shangtong Zhang, Jianlei Yang, Xiaotao Jia, Zhaohao Wang, Gang Qu, Weisheng Zhao
2023	J	`jnl`	Improving Monte Carlo Evaluation with Offline Data. CoRR Shuze Daniel Liu, Shangtong Zhang
2023	A*	`conf`	On the Convergence of SARSA with Linear Function Approximation. ICML Shangtong Zhang, Remi Tachet des Combes, Romain Laroche
2022	A	`conf`	A Deeper Look at Discounting Mismatch in Actor-Critic Algorithms. AAMAS Shangtong Zhang, Romain Laroche, Harm van Seijen, Shimon Whiteson, Remi Tachet des Combes
2022	J	`jnl`	Global Optimality and Finite Sample Analysis of Softmax Off-Policy Actor Critic under State Distribution Mismatch. J. Mach. Learn. Res. Shangtong Zhang, Remi Tachet des Combes, Romain Laroche
2022	A*	`conf`	Learning Expected Emphatic Traces for Deep RL. AAAI Ray Jiang, Shangtong Zhang, Veronica Chelu, Adam White, Hado van Hasselt
2022	J	`jnl`	On the Chattering of SARSA with Linear Function Approximation. CoRR Shangtong Zhang, Remi Tachet des Combes, Romain Laroche
2022	J	`jnl`	Truncated Emphatic Temporal Difference Methods for Prediction and Control. J. Mach. Learn. Res. Shangtong Zhang, Shimon Whiteson
2021	A*	`conf`	Average-Reward Off-Policy Policy Evaluation with Function Approximation. ICML Shangtong Zhang, Yi Wan, Richard S. Sutton, Shimon Whiteson
2021	J	`jnl`	Average-Reward Off-Policy Policy Evaluation with Function Approximation. CoRR Shangtong Zhang, Yi Wan, Richard S. Sutton, Shimon Whiteson
2021	A*	`conf`	Breaking the Deadly Triad with a Target Network. ICML Shangtong Zhang, Hengshuai Yao, Shimon Whiteson
2021	J	`jnl`	Breaking the Deadly Triad with a Target Network. CoRR Shangtong Zhang, Hengshuai Yao, Shimon Whiteson
2021	A*	`conf`	Deep Residual Reinforcement Learning (Extended Abstract). IJCAI Shangtong Zhang, Wendelin Boehmer, Shimon Whiteson
2021	J	`jnl`	Global Optimality and Finite Sample Analysis of Softmax Off-Policy Actor Critic under State Distribution Mismatch. CoRR Shangtong Zhang, Remi Tachet des Combes, Romain Laroche
2021	J	`jnl`	Learning Expected Emphatic Traces for Deep RL. CoRR Ray Jiang, Shangtong Zhang, Veronica Chelu, Adam White, Hado van Hasselt
2021	A*	`conf`	Mean-Variance Policy Iteration for Risk-Averse Reinforcement Learning. AAAI Shangtong Zhang, Bo Liu, Shimon Whiteson
2021	J	`jnl`	Truncated Emphatic Temporal Difference Methods for Prediction and Control. CoRR Shangtong Zhang, Shimon Whiteson
2020	J	`jnl`	A Deeper Look at Discounting Mismatch in Actor-Critic Algorithms. CoRR Shangtong Zhang, Romain Laroche, Harm van Seijen, Shimon Whiteson, Remi Tachet des Combes
2020	A	`conf`	Deep Residual Reinforcement Learning. AAMAS Shangtong Zhang, Wendelin Boehmer, Shimon Whiteson
2020	A*	`conf`	GradientDICE: Rethinking Generalized Offline Estimation of Stationary Values. ICML Shangtong Zhang, Bo Liu, Shimon Whiteson
2020	J	`jnl`	GradientDICE: Rethinking Generalized Offline Estimation of Stationary Values. CoRR Shangtong Zhang, Bo Liu, Shimon Whiteson
2020	A*	`conf`	Learning Retrospective Knowledge with Reverse Reinforcement Learning. NeurIPS Shangtong Zhang, Vivek Veeriah, Shimon Whiteson
2020	J	`jnl`	Learning Retrospective Knowledge with Reverse Reinforcement Learning. CoRR Shangtong Zhang, Vivek Veeriah, Shimon Whiteson
2020	A*	`conf`	Mega-Reward: Achieving Human-Level Play without Extrinsic Rewards. AAAI Yuhang Song, Jianyi Wang, Thomas Lukasiewicz, Zhenghua Xu, Shangtong Zhang, Andrzej Wojcicki, Mai Xu
2020	J	`jnl`	Per-Step Reward: A New Perspective for Risk-Averse Reinforcement Learning. CoRR Shangtong Zhang, Bo Liu, Shimon Whiteson
2020	A*	`conf`	Provably Convergent Two-Timescale Off-Policy Actor-Critic with Function Approximation. ICML Shangtong Zhang, Bo Liu, Hengshuai Yao, Shimon Whiteson
2019	A*	`conf`	ACE: An Actor Ensemble Algorithm for Continuous Control with Tree Search. AAAI Shangtong Zhang, Hengshuai Yao
2019	A*	`conf`	DAC: The Double Actor-Critic Architecture for Learning Options. NeurIPS Shangtong Zhang, Shimon Whiteson
2019	J	`jnl`	DAC: The Double Actor-Critic Architecture for Learning Options. CoRR Shangtong Zhang, Shimon Whiteson
2019	J	`jnl`	Deep Residual Reinforcement Learning. CoRR Shangtong Zhang, Wendelin Boehmer, Shimon Whiteson
2019	J	`jnl`	Distributional Reinforcement Learning for Efficient Exploration. CoRR Borislav Mavrin, Shangtong Zhang, Hengshuai Yao, Linglong Kong, Kaiwen Wu, Yaoliang Yu
2019	A	`conf`	Exploration in the Face of Parametric and Intrinsic Uncertainties. AAMAS Borislav Mavrin, Shangtong Zhang, Hengshuai Yao, Linglong Kong
2019	A*	`conf`	Generalized Off-Policy Actor-Critic. NeurIPS Shangtong Zhang, Wendelin Boehmer, Shimon Whiteson
2019	J	`jnl`	Generalized Off-Policy Actor-Critic. CoRR Shangtong Zhang, Wendelin Boehmer, Shimon Whiteson
2019	J	`jnl`	Mega-Reward: Achieving Human-Level Play without Extrinsic Rewards. CoRR Yuhang Song, Jianyi Wang, Thomas Lukasiewicz, Zhenghua Xu, Shangtong Zhang, Mai Xu
2019	J	`jnl`	Provably Convergent Off-Policy Actor-Critic with Function Approximation. CoRR Shangtong Zhang, Bo Liu, Hengshuai Yao, Shimon Whiteson
2019	A*	`conf`	QUOTA: The Quantile Option Architecture for Reinforcement Learning. AAAI Shangtong Zhang, Hengshuai Yao
2018	J	`jnl`	ACE: An Actor Ensemble Algorithm for Continuous Control with Tree Search. CoRR Shangtong Zhang, Hao Chen, Hengshuai Yao
2018	J	`jnl`	QUOTA: The Quantile Option Architecture for Reinforcement Learning. CoRR Shangtong Zhang, Borislav Mavrin, Linglong Kong, Bo Liu, Hengshuai Yao
2018	J	`jnl`	mlpack 3: a fast, flexible machine learning library. J. Open Source Softw. Ryan R. Curtin, Marcus Edel, Mikhail Lozhnikov, Yannis Mentekidis, Sumedh Ghaisas, Shangtong Zhang
2017	J	`jnl`	A Deeper Look at Experience Replay. CoRR Shangtong Zhang, Richard S. Sutton
2017	J	`jnl`	Comparing Deep Reinforcement Learning and Evolutionary Methods in Continuous Control. CoRR Shangtong Zhang, Osmar R. Zaïane
2017	—	`conf`	Crossprop: Learning Representations by Stochastic Meta-Gradient Descent in Neural Networks. ECML/PKDD (1) Vivek Veeriah, Shangtong Zhang, Richard S. Sutton
2015	B	`conf`	A Deep Neural Network for Modeling Music. ICMR Pengjing Zhang, Xiaoqing Zheng, Wenqiang Zhang, Siyan Li, Sheng Qian, Wenqi He, Shangtong Zhang, Ziyuan Wang