Exploration Through Reward Biasing: Reward-Biased Maximum Likelihood Estimation for Stochastic Multi-Armed Bandits. - Xi Liu 011; Ping-Chun Hsieh; Yu-Heng Hung; Anirban Bhattacharya; P. R. Kumar 001 (ICML, 2020)

Reward-Biased Maximum Likelihood Estimation for Linear Stochastic Bandits. - Yu-Heng Hung; Ping-Chun Hsieh; Xi Liu 011; P. R. Kumar 001 (AAAI, 2021)

Neural Contextual Bandits via Reward-Biased Maximum Likelihood Estimation. - Yu-Heng Hung; Ping-Chun Hsieh (CoRR, 2022)

Reward-Biased Maximum Likelihood Estimation for Neural Contextual Bandits: A Distributional Learning Perspective. - Yu-Heng Hung; Ping-Chun Hsieh (AAAI, 2023)

Social Robots for Older Adults in Medical Contexts. - Wen-I Lu; Yu-Wei Chen; Chin-Chen Shen; Ping-Hsuan Tsai; Yun-Tung Chu; Yu-Heng Hung; Shih-Yi Chien; Joyce Lee; Shiau-Fang Chao (HCI (3), 2023)

Value-Biased Maximum Likelihood Estimation for Model-based Reinforcement Learning in Discounted Linear MDPs. - Yu-Heng Hung; Ping-Chun Hsieh; Akshay Mete; P. R. Kumar 001 (CoRR, 2023)

BOFormer: Learning to Solve Multi-Objective Bayesian Optimization via Non-Markovian RL. - Yu-Heng Hung; Kai-Jie Lin; Yu-Heng Lin; Chien-Yi Wang; Cheng Sun; Ping-Chun Hsieh (ICLR, 2025)

Plan2Align: Predictive Planning Based Test-Time Preference Alignment in Paragraph-Level Machine Translation. - Kuang-Da Wang; Teng-Ruei Chen; Yu-Heng Hung; Shuoyang Ding; Yueh-Hua Wu; Yu-Chiang Frank Wang; Chao-Han Huck Yang; Wen-Chih Peng; Ping-Chun Hsieh (CoRR, 2025)