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2020 – today
- 2024
[c30]Nai-Chieh Huang, Ping-Chun Hsieh
, Kuo-Hao Ho, I-Chen Wu:
PPO-Clip Attains Global Optimality: Towards Deeper Understandings of Clipping. AAAI 2024: 12600-12607- [c29]Yen-Ju Chen, Nai-Chieh Huang, Ching-pei Lee, Ping-Chun Hsieh:
Accelerated Policy Gradient: On the Convergence Rates of the Nesterov Momentum for Reinforcement Learning. ICML 2024 - [c28]Yun-Hsuan Lien, Ping-Chun Hsieh, Tzu-Mao Li, Yu-Shuen Wang:
Enhancing Value Function Estimation through First-Order State-Action Dynamics in Offline Reinforcement Learning. ICML 2024 - [c27]Kuang-Da Wang, Wei-Yao Wang, Ping-Chun Hsieh, Wen-Chih Peng:
Offline Imitation of Badminton Player Behavior via Experiential Contexts and Brownian Motion. ECML/PKDD (10) 2024: 348-364 - [i24]Kuang-Da Wang, Wei-Yao Wang, Ping-Chun Hsieh, Wen-Chih Peng:
Offline Imitation of Badminton Player Behavior via Experiential Contexts and Brownian Motion. CoRR abs/2403.12406 (2024) - [i23]He-Hao Liao, Yan-Tsung Peng, Wen-Tao Chu, Ping-Chun Hsieh, Chung-Chi Tsai:
Image Deraining via Self-supervised Reinforcement Learning. CoRR abs/2403.18270 (2024) - [i22]Chun-Mao Lai, Hsiang-Chun Wang, Ping-Chun Hsieh, Yu-Chiang Frank Wang, Min-Hung Chen, Shao-Hua Sun:
Diffusion-Reward Adversarial Imitation Learning. CoRR abs/2405.16194 (2024) - 2023
- [c26]Yu-Heng Hung, Ping-Chun Hsieh:
Reward-Biased Maximum Likelihood Estimation for Neural Contextual Bandits: A Distributional Learning Perspective. AAAI 2023: 7944-7952 - [c25]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 - [c24]Hsin-En Su, Yen-Ju Chen, Ping-Chun Hsieh, Xi Liu:
Coordinate Ascent for Off-Policy RL with Global Convergence Guarantees. AISTATS 2023: 1331-1378 - [c23]Wei Hung, Bo-Kai Huang, Ping-Chun Hsieh, Xi Liu:
Q-Pensieve: Boosting Sample Efficiency of Multi-Objective RL Through Memory Sharing of Q-Snapshots. ICLR 2023 - [c22]Yun-Hsuan Lien, Ping-Chun Hsieh, Yu-Shuen Wang:
Revisiting Domain Randomization via Relaxed State-Adversarial Policy Optimization. ICML 2023: 20939-20949 - [i21]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. CoRR abs/2309.15484 (2023) - [i20]Yu-Heng Hung, Ping-Chun Hsieh, Akshay Mete, P. R. Kumar:
Value-Biased Maximum Likelihood Estimation for Model-based Reinforcement Learning in Discounted Linear MDPs. CoRR abs/2310.11515 (2023) - [i19]Yen-Ju Chen, Nai-Chieh Huang, Ping-Chun Hsieh:
Accelerated Policy Gradient: On the Nesterov Momentum for Reinforcement Learning. CoRR abs/2310.11897 (2023) - [i18]Nai-Chieh Huang, Ping-Chun Hsieh, Kuo-Hao Ho, I-Chen Wu:
PPO-Clip Attains Global Optimality: Towards Deeper Understandings of Clipping. CoRR abs/2312.12065 (2023) - 2022
- [c21]Cheng-Yu Wu, Li-Hsing Yen, Ping-Chun Hsieh, Chien-Chao Tseng:
Deterministic Bandwidth-Based Packet-Level Traffic Splitting for Datacenter Networks. APNOMS 2022: 1-6 - [c20]Yung-Han Ho, Chia-Hao Kao, Wen-Hsiao Peng, Ping-Chun Hsieh:
Neural Frank-Wolfe Policy Optimization for Region-of-Interest Intra-Frame Coding with HEVC/H.265. VCIP 2022: 1-5 - [i17]Yu-Heng Hung, Ping-Chun Hsieh:
Neural Contextual Bandits via Reward-Biased Maximum Likelihood Estimation. CoRR abs/2203.04192 (2022) - [i16]Yung-Han Ho, Chia-Hao Kao, Wen-Hsiao Peng, Ping-Chun Hsieh:
Neural Frank-Wolfe Policy Optimization for Region-of-Interest Intra-Frame Coding with HEVC/H.265. CoRR abs/2209.13210 (2022) - [i15]Wei Hung, Bo-Kai Huang, Ping-Chun Hsieh, Xi Liu:
Q-Pensieve: Boosting Sample Efficiency of Multi-Objective RL Through Memory Sharing of Q-Snapshots. CoRR abs/2212.03117 (2022) - [i14]Hsin-En Su, Yen-Ju Chen, Ping-Chun Hsieh, Xi Liu:
Coordinate Ascent for Off-Policy RL with Global Convergence Guarantees. CoRR abs/2212.05237 (2022) - 2021
- [c19]Yu-Heng Hung, Ping-Chun Hsieh, Xi Liu, P. R. Kumar:
Reward-Biased Maximum Likelihood Estimation for Linear Stochastic Bandits. AAAI 2021: 7874-7882 - [c18]Daojing Guo, Ping-Chun Hsieh, I-Hong Hou:
Optimal Wireless Scheduling for Remote Sensing through Brownian Approximation. INFOCOM 2021: 1-10 - [c17]Khaled Nakhleh, Santosh Ganji, Ping-Chun Hsieh, I-Hong Hou, Srinivas Shakkottai:
NeurWIN: Neural Whittle Index Network For Restless Bandits Via Deep RL. NeurIPS 2021: 828-839 - [c16]Bing-Jing Hsieh, Ping-Chun Hsieh, Xi Liu:
Reinforced Few-Shot Acquisition Function Learning for Bayesian Optimization. NeurIPS 2021: 7718-7731 - [c15]Jyun-Li Lin, Wei Hung, Shang-Hsuan Yang, Ping-Chun Hsieh, Xi Liu:
Escaping from zero gradient: Revisiting action-constrained reinforcement learning via Frank-Wolfe policy optimization. UAI 2021: 397-407 - [i13]Jyun-Li Lin, Wei Hung, Shang-Hsuan Yang, Ping-Chun Hsieh, Xi Liu:
Escaping from Zero Gradient: Revisiting Action-Constrained Reinforcement Learning via Frank-Wolfe Policy Optimization. CoRR abs/2102.11055 (2021) - [i12]Bing-Jing Hsieh, Ping-Chun Hsieh, Xi Liu:
Reinforced Few-Shot Acquisition Function Learning for Bayesian Optimization. CoRR abs/2106.04335 (2021) - [i11]Khaled Nakhleh, Santosh Ganji, Ping-Chun Hsieh, I-Hong Hou, Srinivas Shakkottai:
NeurWIN: Neural Whittle Index Network For Restless Bandits Via Deep RL. CoRR abs/2110.02128 (2021) - [i10]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
- [c14]Xi Liu, Ping-Chun Hsieh, Yu-Heng Hung, Anirban Bhattacharya, P. R. Kumar:
Exploration Through Reward Biasing: Reward-Biased Maximum Likelihood Estimation for Stochastic Multi-Armed Bandits. ICML 2020: 6248-6258 - [c13]Ping-Chun Hsieh, Xi Liu, I-Hong Hou:
Fresher content or smoother playback?: a brownian-approximation framework for scheduling real-time wireless video streams. MobiHoc 2020: 41-50 - [i9]Xi Liu, Li Li, Ping-Chun Hsieh, Muhe Xie, Yong Ge, Rui Chen:
Developing Multi-Task Recommendations with Long-Term Rewards via Policy Distilled Reinforcement Learning. CoRR abs/2001.09595 (2020) - [i8]Yu-Heng Hung, Ping-Chun Hsieh, Xi Liu, P. R. Kumar:
Reward-Biased Maximum Likelihood Estimation for Linear Stochastic Bandits. CoRR abs/2010.04091 (2020)
2010 – 2019
- 2019
- [c12]Ping-Chun Hsieh, Xi Liu, Anirban Bhattacharya, P. R. Kumar:
Stay With Me: Lifetime Maximization Through Heteroscedastic Linear Bandits With Reneging. ICML 2019: 2800-2809 - [c11]Xi Liu, Ping-Chun Hsieh, Nick Duffield, Rui Chen, Muhe Xie, Xidao Wen:
Real-Time Streaming Graph Embedding Through Local Actions. WWW (Companion Volume) 2019: 285-293 - [i7]Xi Liu, Ping-Chun Hsieh, Anirban Bhattacharya, P. R. Kumar:
Bandit Learning Through Biased Maximum Likelihood Estimation. CoRR abs/1907.01287 (2019) - [i6]Ping-Chun Hsieh, Xi Liu, I-Hong Hou:
Fresher Content or Smoother Playback? A Brownian-Approximation Framework for Real-Time Video Delivery in Wireless Networks. CoRR abs/1911.00902 (2019) - 2018
- [j2]Ping-Chun Hsieh, I-Hong Hou:
Heavy-Traffic Analysis of QoE Optimality for On-Demand Video Streams Over Fading Channels. IEEE/ACM Trans. Netw. 26(4): 1768-1781 (2018) - [c10]Xi Liu, Ping-Chun Hsieh, P. R. Kumar:
Safe Intersection Management for Mixed Transportation Systems with Human-Driven and Autonomous Vehicles. Allerton 2018: 834-841 - [c9]Ping-Chun Hsieh, Yupeng Jia, Darwin Parra, Prabha Aithal:
An Experimental Study on Coverage Enhancement of LTE Cat-M1 for Machine-Type Communication. ICC 2018: 1-5 - [c8]Ping-Chun Hsieh, I-Hong Hou:
A Decentralized Medium Access Protocol for Real-Time Wireless Ad Hoc Networks With Unreliable Transmissions. ICDCS 2018: 972-982 - [c7]Simon Yau, Ping-Chun Hsieh, Rajarshi Bhattacharyya, K. R. Kartic Bhargav, Srinivas Shakkottai, I-Hong Hou, P. R. Kumar:
PULS: Processor-Supported Ultra-Low Latency Scheduling. MobiHoc 2018: 261-270 - [c6]Simon Yau, Ping-Chun Hsieh, Rajarshi Bhattacharyya, K. R. Kartic Bhargav, Srinivas Shakkottai, I-Hong Hou, P. R. Kumar:
PULS: Processor-Supported Ultra-Low Latency Scheduling. MobiHoc 2018: 324-325 - [i5]Xi Liu, Ping-Chun Hsieh, P. R. Kumar:
Safe Intersection Management for Mixed Transportation Systems with Human-Driven and Autonomous Vehicles. CoRR abs/1808.06632 (2018) - [i4]Ping-Chun Hsieh, Xi Liu, Anirban Bhattacharya, P. R. Kumar:
Heteroscedastic Bandits with Reneging. CoRR abs/1810.12418 (2018) - [i3]Xi Liu, Ping-Chun Hsieh, Nick Duffield, Rui Chen, Muhe Xie, Xidao Wen:
Streaming Network Embedding through Local Actions. CoRR abs/1811.05932 (2018) - 2017
- [j1]I-Hong Hou, Ping-Chun Hsieh:
The capacity of QoE for wireless networks with unreliable transmissions. Queueing Syst. Theory Appl. 87(1-2): 131-159 (2017) - [c5]Hsiang-Ting Hong, Tzu-Yu Su, Po-Hsun Lee, Ping-Chun Hsieh, Mian-Jhong Chiu:
VisualLink: Strengthening the Connection between Hearing-impaired Elderly and their Family. CHI Extended Abstracts 2017: 67-73 - [c4]Ping-Chun Hsieh, Xi Liu, Jian Jiao, I-Hong Hou, Yunlong Zhang, P. R. Kumar:
Throughput-Optimal Scheduling for Multi-Hop Networked Transportation Systems With Switch-Over Delay. MobiHoc 2017: 16:1-16:10 - [i2]Ping-Chun Hsieh, I-Hong Hou, Xi Liu:
Delay-Optimal Scheduling for Queueing Systems with Switching Overhead. CoRR abs/1701.03831 (2017) - [i1]Ping-Chun Hsieh, Xi Liu, Jian Jiao, I-Hong Hou, Yunlong Zhang, P. R. Kumar:
Throughput-Optimal Scheduling for Multi-Hop Networked Transportation Systems With Switch-Over Delay. CoRR abs/1701.03991 (2017) - 2016
- [c3]Ping-Chun Hsieh, I-Hong Hou:
Heavy-traffic analysis of QoE optimality for on-demand video streams over fading channels. INFOCOM 2016: 1-9 - 2015
- [c2]I-Hong Hou, Ping-Chun Hsieh:
QoE-Optimal Scheduling for On-Demand Video Streams over Unreliable Wireless Networks. MobiHoc 2015: 207-216 - [c1]Simon Yau, Liang Ge, Ping-Chun Hsieh, I-Hong Hou, Shuguang Cui, P. R. Kumar, Amal Ekbal, Nikhil Kundargi:
WiMAC: Rapid Implementation Platform for User Definable MAC Protocols Through Separation. SIGCOMM 2015: 109-110
Coauthor Index
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last updated on 2024-10-07 22:11 CEST by the dblp team
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