Efficient network coding at relay for relay-assisted network-coding ARQ protocols. - Jung-Chun Kao; Kuo-Hao Ho (APSIPA, 2013)

Prediction of Time Series Data Based on Transformer with Soft Dynamic Time Wrapping. - Kuo-Hao Ho; Pei-Shu Huang; I-Chen Wu; Feng-Jian Wang (ICCE-TW, 2020)

Hinge Policy Optimization: Rethinking Policy Improvement and Reinterpreting PPO. - Hsuan-Yu Yao; Ping-Chun Hsieh; Kuo-Hao Ho; Kai-Chun Hu; Liang-Chun Ouyang; I-Chen Wu (CoRR, 2021)

Towards Human-Like RL: Taming Non-Naturalistic Behavior in Deep RL via Adaptive Behavioral Costs in 3D Games. - Kuo-Hao Ho; Ping-Chun Hsieh; Chiu-Chou Lin; You-Ren Luo; Feng-Jian Wang; I-Chen Wu (ACML, 2023)

Deep Reinforcement Learning Based on Graph Neural Networks for Job-shop Scheduling. - Kuo-Hao Ho; Ji-Han Wu; Fan Chiang; Yuan-Yu Wu; Sheng-I Chen; Ted Kuo; Feng-Jian Wang; I-Chen Wu (ICCE-Taiwan, 2023)

Residual Scheduling: A New Reinforcement Learning Approach to Solving Job Shop Scheduling Problem. - Kuo-Hao Ho; Ruei-Yu Jheng; Ji-Han Wu; Fan Chiang; Yen-Chi Chen; Yuan-Yu Wu; I-Chen Wu (CoRR, 2023)

PPO-Clip Attains Global Optimality: Towards Deeper Understandings of Clipping. - Nai-Chieh Huang; Ping-Chun Hsieh; Kuo-Hao Ho; I-Chen Wu (AAAI, 2024)

Residual Scheduling: A New Reinforcement Learning Approach to Solving Job Shop Scheduling Problem. - Kuo-Hao Ho; Jui-Yu Cheng; Ji-Han Wu; Fan Chiang; Yen-Chi Chen; Yuan-Yu Wu; I-Chen Wu (IEEE Access, 2024)