Yunhao Tang

发表

Exploration by Distributional Reinforcement Learning pdf

Yunhao Tang, Shipra Agrawal, Shipra Agrawal, 2018, IJCAI.

Adaptive Sample-Efficient Blackbox Optimization via ES-active Subspaces pdf

Krzysztof Choromanski, Yunhao Tang, Aldo Pacchiano, 2019, ArXiv.

Orthogonal Estimation of Wasserstein Distances pdf

Krzysztof Choromanski, Adrian Weller, Yunhao Tang, 2019, AISTATS.

Discrete Action On-Policy Learning with Action-Value Critic

Yunhao Tang, Mingzhang Yin, Yuguang Yue, 2020, AISTATS.

Discretizing Continuous Action Space for On-Policy Optimization pdf

Yunhao Tang, Shipra Agrawal, Shipra Agrawal, 2019, AAAI.

Variational Deep Q Network pdf

Yunhao Tang, Alp Kucukelbir, 2017, ArXiv.

Augment-Reinforce-Merge Policy Gradient for Binary Stochastic Policy pdf

Mingyuan Zhou, Yunhao Tang, Mingzhang Yin, 2019, ArXiv.

Taylor Expansion Policy Optimization pdf

Michal Valko, Yunhao Tang, Rémi Munos, 2020, ICML.

From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization

Krzysztof Choromanski, Yunhao Tang, Aldo Pacchiano, 2019, NeurIPS.

Self-Imitation Learning via Generalized Lower Bound Q-learning pdf

Yunhao Tang, 2020, NeurIPS.

Provably Robust Blackbox Optimization for Reinforcement Learning

Atil Iscen, Krzysztof Choromanski, Deepali Jain, 2019, CoRL.

ES-MAML: Simple Hessian-Free Meta Learning pdf

Wenbo Gao, Krzysztof Choromanski, Xingyou Song, 2020, ICLR.

Learning to Score Behaviors for Guided Policy Optimization

Michael I. Jordan, Krzysztof Choromanski, Anna Choromanska, 2020, ICML.

Monte-Carlo Tree Search as Regularized Policy Optimization

Michal Valko, Yunhao Tang, Thomas Hubert, 2020, ICML.

Hindsight Expectation Maximization for Goal-conditioned Reinforcement Learning pdf

Yunhao Tang, Alp Kucukelbir, 2020, ArXiv.

Implicit Policy for Reinforcement Learning pdf

Yunhao Tang, Shipra Agrawal, 2018, ArXiv.

Boosting Trust Region Policy Optimization by Normalizing Flows Policy pdf

Yunhao Tang, Shipra Agrawal, 2018, ArXiv.

Using machine learning approach to predict enzyme family classes by fusing AM-PSE-AAC and PSE-PSSM

Yunhao Tang, 2016 .

Reinforcement Learning for Integer Programming: Learning to Cut

Yunhao Tang, Shipra Agrawal, Yuri Faenza, 2019, ICML.

Practical Nonisotropic Monte Carlo Sampling in High Dimensions via Determinantal Point Processes

Krzysztof Choromanski, Yunhao Tang, Aldo Pacchiano, 2020, AISTATS.

ES-ENAS: Combining Evolution Strategies with Neural Architecture Search at No Extra Cost for Reinforcement Learning pdf

Wenbo Gao, Krzysztof Choromanski, Xingyou Song, 2021, ArXiv.

Behavior-Guided Reinforcement Learning

Michael I. Jordan, Krzysztof Choromanski, Anna Choromanska, 2019 .

Structured Monte Carlo Sampling for Nonisotropic Distributions via Determinantal Point Processes pdf

Krzysztof Choromanski, Yunhao Tang, Aldo Pacchiano, 2019, ArXiv.

Variance Reduction for Evolution Strategies via Structured Control Variates pdf

Krzysztof Choromanski, Yunhao Tang, Alp Kucukelbir, 2019, AISTATS.

Online Hyper-parameter Tuning in Off-policy Learning via Evolutionary Strategies pdf

Krzysztof Choromanski, Yunhao Tang, K. Choromanski, 2020, ArXiv.

Reinforcement Learning with Chromatic Networks for Compact Architecture Search

Wenbo Gao, Krzysztof Choromanski, Xingyou Song, 2019 .

Reinforcement Learning with Chromatic Networks pdf

Wenbo Gao, Krzysztof Choromanski, Xingyou Song, 2019, ArXiv.

KAMA-NNs: Low-dimensional Rotation Based Neural Networks

Krzysztof Choromanski, Jeffrey Pennington, Yunhao Tang, 2019, AISTATS.

Taylor Expansion of Discount Factors

Michal Valko, Yunhao Tang, Mark Rowland, 2021, ICML.

Unifying Gradient Estimators for Meta-Reinforcement Learning via Off-Policy Evaluation pdf

Michal Valko, Yunhao Tang, Tadashi Kozuno, 2021, NeurIPS.

Revisiting Peng's Q(λ) for Modern Reinforcement Learning

Michal Valko, Yunhao Tang, Tadashi Kozuno, 2021, ICML.