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← Authors

Ping-Chun Hsieh

19 papers · 2019–2025 · 8 conferences · across top CS/AI conferences

Achievements

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+8 more ↓ 🐝 Cross-Pollinator (14) πŸƒ Academic Marathon (6) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (8) 🌈 Renaissance Researcher (6)
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Conferences

ICML (6) AAAI (3) ICLR (3) NIPS (3) ACML (1) AISTATS (1) EMNLP (1) UAI (1)

Top co-authors

Xi Liu (7) Wei Hung (4) Shao-Hua Sun (3) Yu-Shuen Wang (2) Yun-Hsuan Lien (2) Nai-Chieh Huang (2) Kuo-Hao Ho (2) Yen-Ju Chen (2) Yu-Heng Hung (2) Anirban Bhattacharya (2)

Keywords

reinforcement learning (4) policy optimization (3) regret bound (3) deep reinforcement learning (2) multi-armed bandit (2) adversarial learning (2) neural network (2) global convergence (2) linear bandit (2) markov decision process (1) domain randomization (1) constrained optimization (1) imitation learning (1) exploration-exploitation tradeoff (1) off-policy reinforcement learning (1) policy learning (1) maximum likelihood estimation (1) off-policy learning (1) machine translation (1) reward function (1)

Papers

Efficient Action-Constrained Reinforcement Learning via Acceptance-Rejection Method and Augmented MDPs ICLR 2025 Action-Constrained Imitation Learning ICML 2025 BOFormer: Learning to Solve Multi-Objective Bayesian Optimization via Non-Markovian RL ICLR 2025 Extending Automatic Machine Translation Evaluation to Book-Length Documents EMNLP 2025 Enhancing Value Function Estimation through First-Order State-Action Dynamics in Offline Reinforcement Learning ICML 2024 Accelerated Policy Gradient: On the Convergence Rates of the Nesterov Momentum for Reinforcement Learning ICML 2024 Diffusion-Reward Adversarial Imitation Learning NIPS 2024 PPO-Clip Attains Global Optimality: Towards Deeper Understandings of Clipping AAAI 2024 Coordinate Ascent for Off-Policy RL with Global Convergence Guarantees AISTATS 2023 Q-Pensieve: Boosting Sample Efficiency of Multi-Objective RL Through Memory Sharing of Q-Snapshots ICLR 2023 Towards Human-Like RL: Taming Non-Naturalistic Behavior in Deep RL via Adaptive Behavioral Costs in 3D Games ACML 2023 Reward-Biased Maximum Likelihood Estimation for Neural Contextual Bandits: A Distributional Learning Perspective AAAI 2023 Revisiting Domain Randomization via Relaxed State-Adversarial Policy Optimization ICML 2023 Escaping from zero gradient: Revisiting action-constrained reinforcement learning via Frank-Wolfe policy optimization UAI 2021 Reinforced Few-Shot Acquisition Function Learning for Bayesian Optimization NIPS 2021 Reward-Biased Maximum Likelihood Estimation for Linear Stochastic Bandits AAAI 2021 NeurWIN: Neural Whittle Index Network For Restless Bandits Via Deep RL NIPS 2021 Exploration Through Reward Biasing: Reward-Biased Maximum Likelihood Estimation for Stochastic Multi-Armed Bandits ICML 2020 Stay With Me: Lifetime Maximization Through Heteroscedastic Linear Bandits With Reneging ICML 2019