Lee, Jonathan

18 publications

AAAI 2025 Cost-Aware Near-Optimal Policy Learning Joy He-Yueya, Jonathan Lee, Matthew Jörke, Emma Brunskill

ICML 2025 EVOLvE: Evaluating and Optimizing LLMs for In-Context Exploration Allen Nie, Yi Su, Bo Chang, Jonathan Lee, Ed H. Chi, Quoc V Le, Minmin Chen

WACV 2025 uLayout: Unified Room Layout Estimation for Perspective and Panoramic Images Jonathan Lee, Bolivar E Solarte, Chin-Hsuan Wu, Jin-Cheng Jhang, Fu-En Wang, Yi-Hsuan Tsai, Min Sun

TMLR 2024 Estimating Optimal Policy Value in Linear Contextual Bandits Beyond Gaussianity Jonathan Lee, Weihao Kong, Aldo Pacchiano, Vidya Muthukumar, Emma Brunskill

NeurIPSW 2024 Information Directed Tree Search: Reasoning and Planning with Language Agents Yash Chandak, HyunJi Nam, Allen Nie, Jonathan Lee, Emma Brunskill

ECCV 2024 Self-Training Room Layout via Geometry-Aware Ray-Casting Bolivar Solarte, Chin-Hsuan Wu, Jin-Cheng Jhang, Jonathan Lee, Yi-Hsuan Tsai, Min Sun

AISTATS 2023 Dueling RL: Reinforcement Learning with Trajectory Preferences Aadirupa Saha, Aldo Pacchiano, Jonathan Lee

NeurIPS 2023 Experiment Planning with Function Approximation Aldo Pacchiano, Jonathan Lee, Emma Brunskill

ICMLW 2023 In-Context Decision-Making from Supervised Pretraining Jonathan Lee, Annie Xie, Aldo Pacchiano, Yash Chandak, Chelsea Finn, Ofir Nachum, Emma Brunskill

ICML 2023 Learning in POMDPs Is Sample-Efficient with Hindsight Observability Jonathan Lee, Alekh Agarwal, Christoph Dann, Tong Zhang

NeurIPS 2023 Supervised Pretraining Can Learn In-Context Reinforcement Learning Jonathan Lee, Annie Xie, Aldo Pacchiano, Yash Chandak, Chelsea Finn, Ofir Nachum, Emma Brunskill

ICML 2022 Model Selection in Batch Policy Optimization Jonathan Lee, George Tucker, Ofir Nachum, Bo Dai

AISTATS 2021 Online Model Selection for Reinforcement Learning with Function Approximation Jonathan Lee, Aldo Pacchiano, Vidya Muthukumar, Weihao Kong, Emma Brunskill

ICML 2020 Accelerated Message Passing for Entropy-Regularized MAP Inference Jonathan Lee, Aldo Pacchiano, Peter Bartlett, Michael Jordan

AISTATS 2020 Convergence Rates of Smooth Message Passing with Rounding in Entropy-Regularized MAP Inference Jonathan Lee, Aldo Pacchiano, Michael Jordan

AISTATS 2020 Online Learning with Continuous Variations: Dynamic Regret and Reductions Ching-An Cheng, Jonathan Lee, Ken Goldberg, Byron Boots

CoRL 2019 On-Policy Robot Imitation Learning from a Converging Supervisor Ashwin Balakrishna, Brijen Thananjeyan, Jonathan Lee, Felix Li, Arsh Zahed, Joseph E. Gonzalez, Ken Goldberg

CoRL 2017 DART: Noise Injection for Robust Imitation Learning Michael Laskey, Jonathan Lee, Roy Fox, Anca D. Dragan, Ken Goldberg