Shangtong Zhang

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 48

Top Topics

Temporal Difference

Function Approximation

Reinforcement Learning

Top Venues

Publications

Shuze Liu, Shuhang Chen, Shangtong Zhang
The ODE Method for Stochastic Approximation and Reinforcement Learning with Markovian Noise. CoRR (2024)
Jiuqi Wang, Ethan Blaser, Hadi Daneshmand, Shangtong Zhang
Transformers Learn Temporal Difference Methods for In-Context Reinforcement Learning. CoRR (2024)
Shangtong Zhang
A New Challenge in Policy Evaluation. AAAI (2023)
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
AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning. CoRR (2023)
Shangtong Zhang, Remi Tachet des Combes, Romain Laroche
On the Convergence of SARSA with Linear Function Approximation. ICML (2023)
Xiaochi Qian, Shangtong Zhang
Direct Gradient Temporal Difference Learning. CoRR (2023)
Shuze Liu, Shangtong Zhang
Improving Monte Carlo Evaluation with Offline Data. CoRR (2023)
Yuntao Wei, Xueyan Wang, Shangtong Zhang, Jianlei Yang, Xiaotao Jia, Zhaohao Wang, Gang Qu, Weisheng Zhao
IMGA: Efficient In-Memory Graph Convolution Network Aggregation With Data Flow Optimizations. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42 (12) (2023)
Shangtong Zhang, Shimon Whiteson
Truncated Emphatic Temporal Difference Methods for Prediction and Control. J. Mach. Learn. Res. 23 (2022)
Shangtong Zhang, Remi Tachet des Combes, Romain Laroche
On the Chattering of SARSA with Linear Function Approximation. CoRR (2022)
Shangtong Zhang, Remi Tachet des Combes, Romain Laroche
Global Optimality and Finite Sample Analysis of Softmax Off-Policy Actor Critic under State Distribution Mismatch. J. Mach. Learn. Res. 23 (2022)
Shangtong Zhang, Romain Laroche, Harm van Seijen, Shimon Whiteson, Remi Tachet des Combes
A Deeper Look at Discounting Mismatch in Actor-Critic Algorithms. AAMAS (2022)
Ray Jiang, Shangtong Zhang, Veronica Chelu, Adam White, Hado van Hasselt
Learning Expected Emphatic Traces for Deep RL. AAAI (2022)
Shangtong Zhang, Yi Wan, Richard S. Sutton, Shimon Whiteson
Average-Reward Off-Policy Policy Evaluation with Function Approximation. CoRR (2021)
Shangtong Zhang, Remi Tachet des Combes, Romain Laroche
Global Optimality and Finite Sample Analysis of Softmax Off-Policy Actor Critic under State Distribution Mismatch. CoRR (2021)
Shangtong Zhang, Hengshuai Yao, Shimon Whiteson
Breaking the Deadly Triad with a Target Network. CoRR (2021)
Shangtong Zhang, Yi Wan, Richard S. Sutton, Shimon Whiteson
Average-Reward Off-Policy Policy Evaluation with Function Approximation. ICML (2021)
Shangtong Zhang, Hengshuai Yao, Shimon Whiteson
Breaking the Deadly Triad with a Target Network. ICML (2021)
Shangtong Zhang, Bo Liu, Shimon Whiteson
Mean-Variance Policy Iteration for Risk-Averse Reinforcement Learning. AAAI (2021)
Ray Jiang, Shangtong Zhang, Veronica Chelu, Adam White, Hado van Hasselt
Learning Expected Emphatic Traces for Deep RL. CoRR (2021)
Shangtong Zhang, Wendelin Boehmer, Shimon Whiteson
Deep Residual Reinforcement Learning (Extended Abstract). IJCAI (2021)
Shangtong Zhang, Shimon Whiteson
Truncated Emphatic Temporal Difference Methods for Prediction and Control. CoRR (2021)
Shangtong Zhang, Bo Liu, Shimon Whiteson
Per-Step Reward: A New Perspective for Risk-Averse Reinforcement Learning. CoRR (2020)
Shangtong Zhang, Vivek Veeriah, Shimon Whiteson
Learning Retrospective Knowledge with Reverse Reinforcement Learning. CoRR (2020)
Yuhang Song, Jianyi Wang, Thomas Lukasiewicz, Zhenghua Xu, Shangtong Zhang, Andrzej Wojcicki, Mai Xu
Mega-Reward: Achieving Human-Level Play without Extrinsic Rewards. AAAI (2020)
Shangtong Zhang, Wendelin Boehmer, Shimon Whiteson
Deep Residual Reinforcement Learning. AAMAS (2020)
Shangtong Zhang, Romain Laroche, Harm van Seijen, Shimon Whiteson, Remi Tachet des Combes
A Deeper Look at Discounting Mismatch in Actor-Critic Algorithms. CoRR (2020)
Shangtong Zhang, Bo Liu, Shimon Whiteson
GradientDICE: Rethinking Generalized Offline Estimation of Stationary Values. CoRR (2020)
Shangtong Zhang, Vivek Veeriah, Shimon Whiteson
Learning Retrospective Knowledge with Reverse Reinforcement Learning. NeurIPS (2020)
Shangtong Zhang, Bo Liu, Hengshuai Yao, Shimon Whiteson
Provably Convergent Two-Timescale Off-Policy Actor-Critic with Function Approximation. ICML (2020)
Shangtong Zhang, Bo Liu, Shimon Whiteson
GradientDICE: Rethinking Generalized Offline Estimation of Stationary Values. ICML (2020)
Borislav Mavrin, Shangtong Zhang, Hengshuai Yao, Linglong Kong
Exploration in the Face of Parametric and Intrinsic Uncertainties. AAMAS (2019)
Shangtong Zhang, Hengshuai Yao
ACE: An Actor Ensemble Algorithm for Continuous Control with Tree Search. AAAI (2019)
Shangtong Zhang, Shimon Whiteson
DAC: The Double Actor-Critic Architecture for Learning Options. NeurIPS (2019)
Shangtong Zhang, Wendelin Boehmer, Shimon Whiteson
Generalized Off-Policy Actor-Critic. CoRR (2019)
Borislav Mavrin, Shangtong Zhang, Hengshuai Yao, Linglong Kong, Kaiwen Wu, Yaoliang Yu
Distributional Reinforcement Learning for Efficient Exploration. CoRR (2019)
Yuhang Song, Jianyi Wang, Thomas Lukasiewicz, Zhenghua Xu, Shangtong Zhang, Mai Xu
Mega-Reward: Achieving Human-Level Play without Extrinsic Rewards. CoRR (2019)
Shangtong Zhang, Shimon Whiteson
DAC: The Double Actor-Critic Architecture for Learning Options. CoRR (2019)
Shangtong Zhang, Wendelin Boehmer, Shimon Whiteson
Deep Residual Reinforcement Learning. CoRR (2019)
Shangtong Zhang, Hengshuai Yao
QUOTA: The Quantile Option Architecture for Reinforcement Learning. AAAI (2019)
Shangtong Zhang, Wendelin Boehmer, Shimon Whiteson
Generalized Off-Policy Actor-Critic. NeurIPS (2019)
Shangtong Zhang, Bo Liu, Hengshuai Yao, Shimon Whiteson
Provably Convergent Off-Policy Actor-Critic with Function Approximation. CoRR (2019)
Shangtong Zhang, Borislav Mavrin, Linglong Kong, Bo Liu, Hengshuai Yao
QUOTA: The Quantile Option Architecture for Reinforcement Learning. CoRR (2018)
Ryan R. Curtin, Marcus Edel, Mikhail Lozhnikov, Yannis Mentekidis, Sumedh Ghaisas, Shangtong Zhang
mlpack 3: a fast, flexible machine learning library. J. Open Source Softw. 3 (26) (2018)
Shangtong Zhang, Hao Chen, Hengshuai Yao
ACE: An Actor Ensemble Algorithm for Continuous Control with Tree Search. CoRR (2018)
Shangtong Zhang, Richard S. Sutton
A Deeper Look at Experience Replay. CoRR (2017)
Shangtong Zhang, Osmar R. Zaïane
Comparing Deep Reinforcement Learning and Evolutionary Methods in Continuous Control. CoRR (2017)
Vivek Veeriah, Shangtong Zhang, Richard S. Sutton
Crossprop: Learning Representations by Stochastic Meta-Gradient Descent in Neural Networks. ECML/PKDD (1) (2017)
Pengjing Zhang, Xiaoqing Zheng, Wenqiang Zhang, Siyan Li, Sheng Qian, Wenqi He, Shangtong Zhang, Ziyuan Wang
A Deep Neural Network for Modeling Music. ICMR (2015)