Hengshuai Yao

According to our database, Hengshuai Yao authored at least 49 papers between 2006 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Careful at Estimation and Bold at Exploration.

Xing Chen, Yijun Liu, Zhaogeng Liu, Hechang Chen, Hengshuai Yao, Yi Chang

CoRR, 2023

Baird Counterexample Is Solved: with an example of How to Debug a Two-time-scale Algorithm.

Hengshuai Yao

CoRR, 2023

A new Gradient TD Algorithm with only One Step-size: Convergence Rate Analysis using L-λ Smoothness.

Hengshuai Yao

CoRR, 2023

The Sufficiency of Off-Policyness and Soft Clipping: PPO Is Still Insufficient according to an Off-Policy Measure.

Xing Chen, Dongcui Diao, Hechang Chen, Hengshuai Yao, Haiyin Piao, Zhixiao Sun, Zhiwei Yang, Randy Goebel, Bei Jiang, Yi Chang

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

The Vanishing Decision Boundary Complexity and the Strong First Component.

Hengshuai Yao

CoRR, 2022

Class Interference of Deep Neural Networks.

Dongcui Diao, Hengshuai Yao, Bei Jiang

CoRR, 2022

Sigmoidally Preconditioned Off-policy Learning: a new exploration method for reinforcement learning.

Xing Chen, Dongcui Diao, Hechang Chen, Hengshuai Yao, Jielong Yang, Haiyin Piao, Zhixiao Sun, Bei Jiang, Yi Chang

CoRR, 2022

Learning to Accelerate by the Methods of Step-size Planning.

Hengshuai Yao

CoRR, 2022

Understanding and mitigating the limitations of prioritized experience replay.

Yangchen Pan, Jincheng Mei, Amir-massoud Farahmand, Martha White, Hengshuai Yao, Mohsen Rohani, Jun Luo

Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021

A Multi-Component Framework for the Analysis and Design of Explainable Artificial Intelligence.

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

Mach. Learn. Knowl. Extr., 2021

Explainable Artificial Intelligence for Autonomous Driving: A Comprehensive Overview and Field Guide for Future Research Directions.

Shahin Atakishiyev, Mohammad Salameh, Hengshuai Yao, Randy Goebel

CoRR, 2021

Towards safe, explainable, and regulated autonomous driving.

Shahin Atakishiyev, Mohammad Salameh, Hengshuai Yao, Randy Goebel

CoRR, 2021

Exploring the Robustness of Distributional Reinforcement Learning against Noisy State Observations.

Ke Sun, Yi Liu, Yingnan Zhao, Hengshuai Yao, Shangling Jui, Linglong Kong

CoRR, 2021

Exploring Neural Architecture Search Space via Deep Deterministic Sampling.

Keith G. Mills, Mohammad Salameh, Di Niu, Fred X. Han, Seyed Saeed Changiz Rezaei, Hengshuai Yao, Wei Lu, Shuo Lian, Shangling Jui

IEEE Access, 2021

Breaking the Deadly Triad with a Target Network.

Shangtong Zhang, Hengshuai Yao, Shimon Whiteson

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Variance-Reduced Off-Policy Memory-Efficient Policy Search.

Daoming Lyu, Qi Qi, Mohammad Ghavamzadeh, Hengshuai Yao, Tianbao Yang, Bo Liu

CoRR, 2020

Beyond Prioritized Replay: Sampling States in Model-Based RL via Simulated Priorities.

Jincheng Mei, Yangchen Pan, Martha White, Amir-massoud Farahmand, Hengshuai Yao

CoRR, 2020

Towards a practical measure of interference for reinforcement learning.

Vincent Liu, Adam White, Hengshuai Yao, Martha White

CoRR, 2020

Weakly Supervised Few-shot Object Segmentation using Co-Attention with Visual and Semantic Inputs.

Mennatullah Siam, Naren Doraiswamy, Boris N. Oreshkin, Hengshuai Yao, Martin Jägersand

CoRR, 2020

Weakly Supervised Few-shot Object Segmentation using Co-Attention with Visual and Semantic Embeddings.

Mennatullah Siam, Naren Doraiswamy, Boris N. Oreshkin, Hengshuai Yao, Martin Jägersand

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Mapless Navigation among Dynamics with Social-safety-awareness: a reinforcement learning approach from 2D laser scans.

Jun Jin, Nhat M. Nguyen, Nazmus Sakib, Daniel Graves, Hengshuai Yao, Martin Jägersand

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Provably Convergent Two-Timescale Off-Policy Actor-Critic with Function Approximation.

Shangtong Zhang, Bo Liu, Hengshuai Yao, Shimon Whiteson

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

One-Shot Weakly Supervised Video Object Segmentation.

Mennatullah Siam, Naren Doraiswamy, Boris N. Oreshkin, Hengshuai Yao, Martin Jägersand

CoRR, 2019

Provably Convergent Off-Policy Actor-Critic with Function Approximation.

Shangtong Zhang, Bo Liu, Hengshuai Yao, Shimon Whiteson

CoRR, 2019

Is Fast Adaptation All You Need?

Khurram Javed, Hengshuai Yao, Martha White

CoRR, 2019

Distributional Reinforcement Learning for Efficient Exploration.

Borislav Mavrin, Shangtong Zhang, Hengshuai Yao, Linglong Kong, Kaiwen Wu, Yaoliang Yu

CoRR, 2019

Reinforcing Classical Planning for Adversary Driving Scenarios.

Nazmus Sakib, Hengshuai Yao, Hong Zhang

CoRR, 2019

Deep Reinforcement Learning with Decorrelation.

Borislav Mavrin, Hengshuai Yao, Linglong Kong

CoRR, 2019

Hill Climbing on Value Estimates for Search-control in Dyna.

Yangchen Pan, Hengshuai Yao, Amir-massoud Farahmand, Martha White

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Distributional Reinforcement Learning for Efficient Exploration.

Borislav Mavrin, Hengshuai Yao, Linglong Kong, Kaiwen Wu, Yaoliang Yu

Proceedings of the 36th International Conference on Machine Learning, 2019

M-estimation in Low-Rank Matrix Factorization: A General Framework.

Wei Tu, Peng Liu, Jingyu Zhao, Yi Liu, Linglong Kong, Guodong Li, Bei Jiang, Guangjian Tian, Hengshuai Yao

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Exploration in the Face of Parametric and Intrinsic Uncertainties.

Borislav Mavrin, Shangtong Zhang, Hengshuai Yao, Linglong Kong

Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

QUOTA: The Quantile Option Architecture for Reinforcement Learning.

Shangtong Zhang, Hengshuai Yao

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

ACE: An Actor Ensemble Algorithm for Continuous Control with Tree Search.

Shangtong Zhang, Hengshuai Yao

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

ACE: An Actor Ensemble Algorithm for Continuous Control with Tree Search.

Shangtong Zhang, Hao Chen, Hengshuai Yao

CoRR, 2018

QUOTA: The Quantile Option Architecture for Reinforcement Learning.

Shangtong Zhang, Borislav Mavrin, Linglong Kong, Bo Liu, Hengshuai Yao

CoRR, 2018

Negative Log Likelihood Ratio Loss for Deep Neural Network Classification.

Donglai Zhu, Hengshuai Yao, Bei Jiang, Peng Yu

CoRR, 2018

Practical Issues of Action-Conditioned Next Image Prediction.

Donglai Zhu, Hao Chen, Hengshuai Yao, Masoud S. Nosrati, Peyman Yadmellat, Yunfei Zhang

Proceedings of the 21st International Conference on Intelligent Transportation Systems, 2018

2014

Learning to predict trending queries: classification - based.

Chi-Hoon Lee, Hengshuai Yao, Xu He, Su Han Chan, JieYang Chang, Farzin Maghoul

Proceedings of the 23rd International World Wide Web Conference, 2014

Universal Option Models.

Hengshuai Yao, Csaba Szepesvári, Richard S. Sutton, Joseph Modayil, Shalabh Bhatnagar

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Pseudo-MDPs and factored linear action models.

Hengshuai Yao, Csaba Szepesvári, Bernardo Ávila Pires, Xinhua Zhang

Proceedings of the 2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, 2014

2013

Reinforcement Ranking

Hengshuai Yao, Dale Schuurmans

CoRR, 2013

2012

Discovering and Leveraging the Most Valuable Links for Ranking

Hengshuai Yao

CoRR, 2012

Approximate Policy Iteration with Linear Action Models.

Hengshuai Yao, Csaba Szepesvári

Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2009

Multi-Step Dyna Planning for Policy Evaluation and Control.

Hengshuai Yao, Richard S. Sutton, Shalabh Bhatnagar, Diao Dongcui, Csaba Szepesvári

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

LMS-2: Towards an algorithm that is as cheap as LMS and almost as efficient as RLS.

Hengshuai Yao, Shalabh Bhatnagar, Csaba Szepesvári

Proceedings of the 48th IEEE Conference on Decision and Control, 2009

2008

Minimal Residual Approaches for Policy Evaluation in Large Sparse Markov Chains.

Hengshuai Yao, Zhi-Qiang Liu

Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2008

Preconditioned temporal difference learning.

Hengshuai Yao, Zhi-Qiang Liu

Proceedings of the Machine Learning, 2008

2006

Historical Temporal Difference Learning: Some Initial Results.

Hengshuai Yao, Diao Dongcui, Zengqi Sun

Proceedings of the Interdisciplinary and Multidisciplinary Research in Computer Science, 2006