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Neural Frank-Wolfe Policy Optimization for Region-of-Interest Intra-Frame Coding with HEVC/H.265


Sep 27, 2022
Yung-Han Ho, Chia-Hao Kao, Wen-Hsiao Peng, Ping-Chun Hsieh

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* Accepted by VCIP 2022. arXiv admin note: text overlap with arXiv:2203.05127 

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Neural Contextual Bandits via Reward-Biased Maximum Likelihood Estimation


Mar 08, 2022
Yu-Heng Hung, Ping-Chun Hsieh

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Hinge Policy Optimization: Rethinking Policy Improvement and Reinterpreting PPO


Oct 26, 2021
Hsuan-Yu Yao, Ping-Chun Hsieh, Kuo-Hao Ho, Kai-Chun Hu, Liang-Chun Ouyang, I-Chen Wu

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* 22 pages, 3 figures 

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NeurWIN: Neural Whittle Index Network For Restless Bandits Via Deep RL


Oct 05, 2021
Khaled Nakhleh, Santosh Ganji, Ping-Chun Hsieh, I-Hong Hou, Srinivas Shakkottai

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Reinforced Few-Shot Acquisition Function Learning for Bayesian Optimization


Jun 08, 2021
Bing-Jing Hsieh, Ping-Chun Hsieh, Xi Liu

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* 21 pages, 8 figures 

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Escaping from Zero Gradient: Revisiting Action-Constrained Reinforcement Learning via Frank-Wolfe Policy Optimization


Feb 22, 2021
Jyun-Li Lin, Wei Hung, Shang-Hsuan Yang, Ping-Chun Hsieh, Xi Liu

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* 18 pages, 6 figures 

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Reward-Biased Maximum Likelihood Estimation for Linear Stochastic Bandits


Oct 08, 2020
Yu-Heng Hung, Ping-Chun Hsieh, Xi Liu, P. R. Kumar

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Developing Multi-Task Recommendations with Long-Term Rewards via Policy Distilled Reinforcement Learning


Jan 27, 2020
Xi Liu, Li Li, Ping-Chun Hsieh, Muhe Xie, Yong Ge, Rui Chen

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Bandit Learning Through Biased Maximum Likelihood Estimation


Jul 23, 2019
Xi Liu, Ping-Chun Hsieh, Anirban Bhattacharya, P. R. Kumar

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* 23 pages, 5 figures 

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