Hengshuai Yao

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 43

Top Topics

Function Approximation

Reinforcement Learning

Practical Issues

Top Venues

Publications

Shahin Atakishiyev, Mohammad Salameh, Hengshuai Yao, Randy Goebel
Explainable Artificial Intelligence for Autonomous Driving: A Comprehensive Overview and Field Guide for Future Research Directions. IEEE Access 12 (2024)
Xing Chen, Yijun Liu, Zhaogeng Liu, Hechang Chen, Hengshuai Yao, Yi Chang
Careful at Estimation and Bold at Exploration. CoRR (2023)
Hengshuai Yao
Baird Counterexample Is Solved: with an example of How to Debug a Two-time-scale Algorithm. CoRR (2023)
Xing Chen, Dongcui Diao, Hechang Chen, Hengshuai Yao, Haiyin Piao, Zhixiao Sun, Zhiwei Yang, Randy Goebel, Bei Jiang, Yi Chang
The Sufficiency of Off-Policyness and Soft Clipping: PPO Is Still Insufficient according to an Off-Policy Measure. AAAI (2023)
Hengshuai Yao
A new Gradient TD Algorithm with only One Step-size: Convergence Rate Analysis using L-λ Smoothness. CoRR (2023)
Yangchen Pan, Jincheng Mei, Amir-massoud Farahmand, Martha White, Hengshuai Yao, Mohsen Rohani, Jun Luo
Understanding and mitigating the limitations of prioritized experience replay. UAI (2022)
Hengshuai Yao
The Vanishing Decision Boundary Complexity and the Strong First Component. CoRR (2022)
Xing Chen, Dongcui Diao, Hechang Chen, Hengshuai Yao, Jielong Yang, Haiyin Piao, Zhixiao Sun, Bei Jiang, Yi Chang
Sigmoidally Preconditioned Off-policy Learning: a new exploration method for reinforcement learning. CoRR (2022)
Hengshuai Yao
Learning to Accelerate by the Methods of Step-size Planning. CoRR (2022)
Dongcui Diao, Hengshuai Yao, Bei Jiang
Class Interference of Deep Neural Networks. CoRR (2022)
Shangtong Zhang, Hengshuai Yao, Shimon Whiteson
Breaking the Deadly Triad with a Target Network. CoRR (2021)
Keith G. Mills, Mohammad Salameh, Di Niu, Fred X. Han, Seyed Saeed Changiz Rezaei, Hengshuai Yao, Wei Lu, Shuo Lian, Shangling Jui
Exploring Neural Architecture Search Space via Deep Deterministic Sampling. IEEE Access 9 (2021)
Ke Sun, Yi Liu, Yingnan Zhao, Hengshuai Yao, Shangling Jui, Linglong Kong
Exploring the Robustness of Distributional Reinforcement Learning against Noisy State Observations. CoRR (2021)
Shangtong Zhang, Hengshuai Yao, Shimon Whiteson
Breaking the Deadly Triad with a Target Network. ICML (2021)
Shahin Atakishiyev, Mohammad Salameh, Hengshuai Yao, Randy Goebel
Explainable Artificial Intelligence for Autonomous Driving: A Comprehensive Overview and Field Guide for Future Research Directions. CoRR (2021)
Mi-Young Kim, Shahin Atakishiyev, Housam Khalifa Bashier Babiker, Nawshad Farruque, Randy Goebel, Osmar R. Zaïane, Mohammad H. Motallebi, Juliano Rabelo, Talat Iqba Syed, Hengshuai Yao, Peter Chun
A Multi-Component Framework for the Analysis and Design of Explainable Artificial Intelligence. Mach. Learn. Knowl. Extr. 3 (4) (2021)
Shahin Atakishiyev, Mohammad Salameh, Hengshuai Yao, Randy Goebel
Towards safe, explainable, and regulated autonomous driving. CoRR (2021)
Daoming Lyu, Qi Qi, Mohammad Ghavamzadeh, Hengshuai Yao, Tianbao Yang, Bo Liu
Variance-Reduced Off-Policy Memory-Efficient Policy Search. CoRR (2020)
Mennatullah Siam, Naren Doraiswamy, Boris N. Oreshkin, Hengshuai Yao, Martin Jägersand
Weakly Supervised Few-shot Object Segmentation using Co-Attention with Visual and Semantic Embeddings. IJCAI (2020)
Jincheng Mei, Yangchen Pan, Martha White, Amir-massoud Farahmand, Hengshuai Yao
Beyond Prioritized Replay: Sampling States in Model-Based RL via Simulated Priorities. CoRR (2020)
Vincent Liu, Adam White, Hengshuai Yao, Martha White
Towards a practical measure of interference for reinforcement learning. CoRR (2020)
Jun Jin, Nhat M. Nguyen, Nazmus Sakib, Daniel Graves, Hengshuai Yao, Martin Jägersand
Mapless Navigation among Dynamics with Social-safety-awareness: a reinforcement learning approach from 2D laser scans. ICRA (2020)
Shangtong Zhang, Bo Liu, Hengshuai Yao, Shimon Whiteson
Provably Convergent Two-Timescale Off-Policy Actor-Critic with Function Approximation. ICML (2020)
Mennatullah Siam, Naren Doraiswamy, Boris N. Oreshkin, Hengshuai Yao, Martin Jägersand
Weakly Supervised Few-shot Object Segmentation using Co-Attention with Visual and Semantic Inputs. CoRR (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)
Borislav Mavrin, Shangtong Zhang, Hengshuai Yao, Linglong Kong, Kaiwen Wu, Yaoliang Yu
Distributional Reinforcement Learning for Efficient Exploration. CoRR (2019)
Yangchen Pan, Hengshuai Yao, Amir-massoud Farahmand, Martha White
Hill Climbing on Value Estimates for Search-control in Dyna. IJCAI (2019)
Jun Jin, Nhat M. Nguyen, Nazmus Sakib, Daniel Graves, Hengshuai Yao, Martin Jägersand
Mapless Navigation among Dynamics with Social-safety-awareness: a reinforcement learning approach from 2D laser scans. CoRR (2019)
Khurram Javed, Hengshuai Yao, Martha White
Is Fast Adaptation All You Need? CoRR (2019)
Borislav Mavrin, Hengshuai Yao, Linglong Kong, Kaiwen Wu, Yaoliang Yu
Distributional Reinforcement Learning for Efficient Exploration. ICML (2019)
Mennatullah Siam, Naren Doraiswamy, Boris N. Oreshkin, Hengshuai Yao, Martin Jägersand
One-Shot Weakly Supervised Video Object Segmentation. CoRR (2019)
Nazmus Sakib, Hengshuai Yao, Hong Zhang
Reinforcing Classical Planning for Adversary Driving Scenarios. CoRR (2019)
Yangchen Pan, Hengshuai Yao, Amir-massoud Farahmand, Martha White
Hill Climbing on Value Estimates for Search-control in Dyna. CoRR (2019)
Wei Tu, Peng Liu, Jingyu Zhao, Yi Liu, Linglong Kong, Guodong Li, Bei Jiang, Guangjian Tian, Hengshuai Yao
M-estimation in Low-Rank Matrix Factorization: A General Framework. ICDM (2019)
Shangtong Zhang, Hengshuai Yao
QUOTA: The Quantile Option Architecture for Reinforcement Learning. AAAI (2019)
Shangtong Zhang, Bo Liu, Hengshuai Yao, Shimon Whiteson
Provably Convergent Off-Policy Actor-Critic with Function Approximation. CoRR (2019)
Borislav Mavrin, Hengshuai Yao, Linglong Kong
Deep Reinforcement Learning with Decorrelation. CoRR (2019)
Donglai Zhu, Hengshuai Yao, Bei Jiang, Peng Yu
Negative Log Likelihood Ratio Loss for Deep Neural Network Classification. CoRR (2018)
Donglai Zhu, Hao Chen, Hengshuai Yao, Masoud S. Nosrati, Peyman Yadmellat, Yunfei Zhang
Practical Issues of Action-Conditioned Next Image Prediction. ITSC (2018)
Shangtong Zhang, Borislav Mavrin, Linglong Kong, Bo Liu, Hengshuai Yao
QUOTA: The Quantile Option Architecture for Reinforcement Learning. CoRR (2018)
Shangtong Zhang, Hao Chen, Hengshuai Yao
ACE: An Actor Ensemble Algorithm for Continuous Control with Tree Search. CoRR (2018)
Donglai Zhu, Hao Chen, Hengshuai Yao, Masoud S. Nosrati, Peyman Yadmellat, Yunfei Zhang
Practical Issues of Action-conditioned Next Image Prediction. CoRR (2018)
Hengshuai Yao, Csaba Szepesvári, Bernardo Ávila Pires, Xinhua Zhang
Pseudo-MDPs and factored linear action models. ADPRL (2014)
Hengshuai Yao, Csaba Szepesvári, Richard S. Sutton, Joseph Modayil, Shalabh Bhatnagar
Universal Option Models. NIPS (2014)
Chi-Hoon Lee, Hengshuai Yao, Xu He, Su Han Chan, JieYang Chang, Farzin Maghoul
Learning to predict trending queries: classification - based. WWW (Companion Volume) (2014)
Hengshuai Yao, Dale Schuurmans
Reinforcement Ranking CoRR (2013)
Hengshuai Yao
Discovering and Leveraging the Most Valuable Links for Ranking CoRR (2012)
Hengshuai Yao, Csaba Szepesvári
Approximate Policy Iteration with Linear Action Models. AAAI (2012)
Hengshuai Yao, Richard S. Sutton, Shalabh Bhatnagar, Diao Dongcui, Csaba Szepesvári
Multi-Step Dyna Planning for Policy Evaluation and Control. NIPS (2009)
Hengshuai Yao, Shalabh Bhatnagar, Csaba Szepesvári
LMS-2: Towards an algorithm that is as cheap as LMS and almost as efficient as RLS. CDC (2009)
Hengshuai Yao, Zhi-Qiang Liu
Preconditioned temporal difference learning. ICML (2008)
Hengshuai Yao, Zhi-Qiang Liu
Minimal Residual Approaches for Policy Evaluation in Large Sparse Markov Chains. ISAIM (2008)
Hengshuai Yao, Diao Dongcui, Zengqi Sun
Historical Temporal Difference Learning: Some Initial Results. IMSCCS (2) (2006)