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Kuo-Hao Ho
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2020 – today
- 2024
- [j1]Kuo-Hao Ho, Jui-Yu Cheng, Ji-Han Wu, Fan Chiang, Yen-Chi Chen, Yuan-Yu Wu, I-Chen Wu
:
Residual Scheduling: A New Reinforcement Learning Approach to Solving Job Shop Scheduling Problem. IEEE Access 12: 14703-14718 (2024) - [c5]Nai-Chieh Huang, Ping-Chun Hsieh
PPO-Clip Attains Global Optimality: Towards Deeper Understandings of Clipping. AAAI 2024: 12600-12607 - 2023
- [c4]Kuo-Hao Ho, Ping-Chun Hsieh, Chiu-Chou Lin, You-Ren Luo, Feng-Jian Wang, I-Chen Wu:
Towards Human-Like RL: Taming Non-Naturalistic Behavior in Deep RL via Adaptive Behavioral Costs in 3D Games. ACML 2023: 438-453 - [c3]Kuo-Hao Ho, Ji-Han Wu, Fan Chiang, Yuan-Yu Wu, Sheng-I Chen, Ted Kuo, Feng-Jian Wang, I-Chen Wu:
Deep Reinforcement Learning Based on Graph Neural Networks for Job-shop Scheduling. ICCE-Taiwan 2023: 805-806 - [i4]Kuo-Hao Ho, Ping-Chun Hsieh
Towards Human-Like RL: Taming Non-Naturalistic Behavior in Deep RL via Adaptive Behavioral Costs in 3D Games. CoRR abs/2309.15484 (2023) - [i3]Kuo-Hao Ho, Ruei-Yu Jheng, Ji-Han Wu, Fan Chiang, Yen-Chi Chen, Yuan-Yu Wu, I-Chen Wu:
Residual Scheduling: A New Reinforcement Learning Approach to Solving Job Shop Scheduling Problem. CoRR abs/2309.15517 (2023) - [i2]Nai-Chieh Huang, Ping-Chun Hsieh
PPO-Clip Attains Global Optimality: Towards Deeper Understandings of Clipping. CoRR abs/2312.12065 (2023) - 2021
- [i1]Hsuan-Yu Yao, Ping-Chun Hsieh, Kuo-Hao Ho, Kai-Chun Hu, Liang-Chun Ouyang, I-Chen Wu:
Hinge Policy Optimization: Rethinking Policy Improvement and Reinterpreting PPO. CoRR abs/2110.13799 (2021) - 2020
- [c2]Kuo-Hao Ho, Pei-Shu Huang, I-Chen Wu
Prediction of Time Series Data Based on Transformer with Soft Dynamic Time Wrapping. ICCE-TW 2020: 1-2
2010 – 2019
- 2013
- [c1]Jung-Chun Kao, Kuo-Hao Ho:
Efficient network coding at relay for relay-assisted network-coding ARQ protocols. APSIPA 2013: 1-4
Coauthor Index
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