Yinlam Chow

32 papers · 2014–2025 · 7 conferences · across top CS/AI conferences

Achievements

+14 more ↓

🐣 Hot Topic Early Bird 🌍 Conference Polyglot (7) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🏃 Academic Marathon (11)

🐝 Cross-Pollinator (8) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🤝 Dynamic Duo (18) 👑 Triple Crown 🌱 Topic Pioneer 🔬 Deep Specialist (12) 🧬 Topic Evolution 🗃️ Keyword Collector (121) 🚀 Conference Pioneer ⚡ Prolific Year (7) 💎 Century Club (32) 🔥 Unstoppable (12) 📈 Trend Setter

Conferences

NIPS (14) ICLR (7) ICML (4) AISTATS (3) IJCAI (2) CORL (1) JMLR (1)

Top co-authors

Mohammad Ghavamzadeh (18) Craig Boutilier (10) Ofir Nachum (7) Guy Tennenholtz (5) Moonkyung Ryu (4) Azamat Tulepbergenov (3) Aviv Tamar (3) Shie Mannor (3) Bo Dai (3) Marco Pavone (3)

Keywords

policy gradient (7) reinforcement learning (6) markov decision process (4) model-based reinforcement learning (4) off-policy evaluation (3) contextual bandit (3) policy optimization (3) conditional value at risk (2) constraint satisfaction (2) regret bound (2) conditional value-at-risk (2) constrained markov decision process (2) sample efficiency (2) importance sampling (2) safe reinforcement learning (2) latent state (2) temporal dynamics (1) markov decision processes (1) variational inference (1) offline reinforcement learning (1)

Papers

Preference Adaptive and Sequential Text-to-Image Generation ICML 2025 Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models ICLR 2025 DynaMITE-RL: A Dynamic Model for Improved Temporal Meta-Reinforcement Learning NIPS 2024 Embedding-Aligned Language Models NIPS 2024 Demystifying Embedding Spaces using Large Language Models ICLR 2024 A Mixture-of-Expert Approach to RL-based Dialogue Management ICLR 2023 Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management NIPS 2023 Efficient Risk-Averse Reinforcement Learning NIPS 2022 Control-Aware Representations for Model-based Reinforcement Learning ICLR 2021 Variational Model-based Policy Optimization IJCAI 2021 Safe Reinforcement Learning with Natural Language Constraints NIPS 2021 Non-Stationary Off-Policy Optimization AISTATS 2021 CoinDICE: Off-Policy Confidence Interval Estimation NIPS 2020 Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control ICLR 2020 Latent Bandits Revisited NIPS 2020 Safe Policy Learning for Continuous Control CORL 2020 Predictive Coding for Locally-Linear Control ICML 2020 CAQL: Continuous Action Q-Learning ICLR 2020 BRPO: Batch Residual Policy Optimization IJCAI 2020 DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections NIPS 2019 Risk-Sensitive Generative Adversarial Imitation Learning AISTATS 2019 Risk-Constrained Reinforcement Learning with Percentile Risk Criteria JMLR 2018 A Block Coordinate Ascent Algorithm for Mean-Variance Optimization NIPS 2018 A Lyapunov-based Approach to Safe Reinforcement Learning NIPS 2018 Imitation Learning from Visual Data with Multiple Intentions ICLR 2018 Path Consistency Learning in Tsallis Entropy Regularized MDPs ICML 2018 More Robust Doubly Robust Off-policy Evaluation ICML 2018 Sequential Multiple Hypothesis Testing with Type I Error Control AISTATS 2017 Safe Policy Improvement by Minimizing Robust Baseline Regret NIPS 2016 Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach NIPS 2015 Policy Gradient for Coherent Risk Measures NIPS 2015 Algorithms for CVaR Optimization in MDPs NIPS 2014