Jonathan Lee

17 papers · 2017–2025 · 9 conferences · across top CS/AI conferences

Achievements

+10 more ↓

🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (9) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🏃 Academic Marathon (8)

🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (9) 🧬 Topic Evolution 👥 Mega-Team (20) 🗃️ Keyword Collector (75) 📈 Trend Setter 💎 Century Club (17) 🔥 Unstoppable (9) 🚀 Conference Pioneer

Conferences

AISTATS (4) ICML (4) CORL (2) NIPS (2) AAAI (1) ECCV (1) EMNLP (1) OSDI (1) WACV (1)

Top co-authors

Aldo Pacchiano (6) Emma Brunskill (4) Ken Goldberg (3) Min Sun (2) Ofir Nachum (2) Quoc V Le (2) Jin-Cheng Jhang (2) Chin-Hsuan Wu (2) Michael Jordan (2) Yi-Hsuan Tsai (2)

Research topics

Reinforcement Learning (1) Robotics (1)

Keywords

reinforcement learning (4) model selection (3) contextual bandit (3) policy learning (3) function approximation (3) imitation learning (2) map inference (2) off-policy learning (2) message passing (2) entropy regularization (2) regret bound (2) linear programming relaxation (2) in-context learning (1) theorem proving (1) mathematical reasoning (1) offline reinforcement learning (1) image segmentation (1) scene understanding (1) bayesian inference (1) benchmark evaluation (1)

Papers

Towards Robust Mathematical Reasoning EMNLP 2025 uLayout: Unified Room Layout Estimation for Perspective and Panoramic Images WACV 2025 EVOLvE: Evaluating and Optimizing LLMs For In-Context Exploration ICML 2025 Cost-Aware Near-Optimal Policy Learning AAAI 2025 Self-Training Room Layout via Geometry-aware Ray-casting ECCV 2024 Dueling RL: Reinforcement Learning with Trajectory Preferences AISTATS 2023 Supervised Pretraining Can Learn In-Context Reinforcement Learning NIPS 2023 Experiment Planning with Function Approximation NIPS 2023 Learning in POMDPs is Sample-Efficient with Hindsight Observability ICML 2023 Model Selection in Batch Policy Optimization ICML 2022 Online Model Selection for Reinforcement Learning with Function Approximation AISTATS 2021 Online Learning with Continuous Variations: Dynamic Regret and Reductions AISTATS 2020 Accelerated Message Passing for Entropy-Regularized MAP Inference ICML 2020 Convergence Rates of Smooth Message Passing with Rounding in Entropy-Regularized MAP Inference AISTATS 2020 On-Policy Robot Imitation Learning from a Converging Supervisor CORL 2019 Proving the correct execution of concurrent services in zero-knowledge OSDI 2018 DART: Noise Injection for Robust Imitation Learning CORL 2017