← Authors

Liyu Chen

19 papers · 2018–2025 · 9 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (6) 🐝 Cross-Pollinator (12) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer πŸ—ΊοΈ Taxonomy Completionist (24) 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (9) πŸƒ Academic Marathon (7) 🀝 Dynamic Duo (10) πŸ† Grand Slam 🧬 Topic Evolution πŸ† Keyword Champion (7) πŸ’Ž Century Club (19) ⚑ Prolific Year (6) πŸ”₯ Unstoppable (5) πŸ—ƒοΈ Keyword Collector (61)

Conferences

ICML (6) NIPS (4) COLT (3) AAAI (1) AISTATS (1) ALT (1) ICLR (1) IJCAI (1) UAI (1)

Top co-authors

Haipeng Luo (10) Rahul Jain (4) Fei Sha (3) Andrea Tirinzoni (2) Tao Sun (2) Mehdi Jafarnia-Jahromi (2) Matteo Pirotta (2) Alessandro Lazaric (2) Chen-Yu Wei (2) Zhiyun Lu (1)

Keywords

stochastic shortest path (7) regret bound (6) reinforcement learning (4) bandit feedback (4) markov decision process (3) regret minimization (3) policy optimization (2) minimax optimal (2) online mirror descent (2) adversarial cost (2) policy gradient (1) image super-resolution (1) dynamic regret (1) transfer learning (1) adversarial learning (1) posterior sampling (1) variance reduction (1) policy learning (1) continuous control (1) multi-agent learning (1)

Papers

Reward-Augmented Data Enhances Direct Preference Alignment of LLMs ICML 2025
Teaching Language Models to Critique via Reinforcement Learning ICML 2025
Effective Diffusion Transformer Architecture for Image Super-Resolution AAAI 2025
$\mathcal{B}$-Coder: Value-Based Deep Reinforcement Learning for Program Synthesis ICLR 2024
Layered State Discovery for Incremental Autonomous Exploration ICML 2023
Posterior sampling-based online learning for the stochastic shortest path model UAI 2023
Reaching Goals is Hard: Settling the Sample Complexity of the Stochastic Shortest Path ALT 2023
Policy Optimization for Stochastic Shortest Path COLT 2022
Follow-the-Perturbed-Leader for Adversarial Markov Decision Processes with Bandit Feedback NIPS 2022
Near-Optimal Goal-Oriented Reinforcement Learning in Non-Stationary Environments NIPS 2022
Policy Learning and Evaluation with Randomized Quasi-Monte Carlo AISTATS 2022
Improved No-Regret Algorithms for Stochastic Shortest Path with Linear MDP ICML 2022
Learning Infinite-horizon Average-reward Markov Decision Process with Constraints ICML 2022
Implicit Finite-Horizon Approximation and Efficient Optimal Algorithms for Stochastic Shortest Path NIPS 2021
Impossible Tuning Made Possible: A New Expert Algorithm and Its Applications COLT 2021
Minimax Regret for Stochastic Shortest Path with Adversarial Costs and Known Transition COLT 2021
Finding the Stochastic Shortest Path with Low Regret: the Adversarial Cost and Unknown Transition Case ICML 2021
Hyper-parameter Tuning under a Budget Constraint IJCAI 2019
Synthesized Policies for Transfer and Adaptation across Tasks and Environments NIPS 2018