Jonathan Lee

29 papers A* 8A 2C 1Misc 2Journal 12Unranked 4
YearRankTypeTitle / Venue / Authors
2025 A* conf
Cost-Aware Near-Optimal Policy Learning.
AAAI
Joy He-Yueya, Jonathan Lee, Matthew Jörke, Emma Brunskill
2025 A* conf
EVOLvE: Evaluating and Optimizing LLMs For In-Context Exploration.
ICML
Allen Nie, Yi Su, Bo Chang, Jonathan Lee, Ed H. Chi, Quoc V. Le, Minmin Chen
2025 A* conf
Towards Robust Mathematical Reasoning.
EMNLP
Thang Luong, Dawsen Hwang, Hoang H. Nguyen, Golnaz Ghiasi, Yuri Chervonyi, Insuk Seo, Junsu Kim, Garrett Bingham, Jonathan Lee, Swaroop Mishra, Alex Zhai, Clara Huiyi Hu, Henryk Michalewski, Jimin Kim, Jeonghyun Ahn, Junhwi Bae, Xingyou Song, Trieu H. Trinh, Quoc V. Le, Junehyuk Jung
2025 J jnl
Towards Robust Mathematical Reasoning.
CoRR
Thang Luong, Dawsen Hwang, Hoang H. Nguyen, Golnaz Ghiasi, Yuri Chervonyi, Insuk Seo, Junsu Kim, Garrett Bingham, Jonathan Lee, Swaroop Mishra, Alex Zhai, Clara Huiyi Hu, Henryk Michalewski, Jimin Kim, Jeonghyun Ahn, Junhwi Bae, Xingyou Song, Trieu H. Trinh, Quoc V. Le, Junehyuk Jung
2024 J jnl
Estimating Optimal Policy Value in Linear Contextual Bandits Beyond Gaussianity.
Trans. Mach. Learn. Res.
Jonathan Lee, Weihao Kong, Aldo Pacchiano, Vidya Muthukumar, Emma Brunskill
2023 A conf
Dueling RL: Reinforcement Learning with Trajectory Preferences.
AISTATS
Aadirupa Saha, Aldo Pacchiano, Jonathan Lee
2023 A* conf
Experiment Planning with Function Approximation.
NeurIPS
Aldo Pacchiano, Jonathan Lee, Emma Brunskill
2023 A* conf
Learning in POMDPs is Sample-Efficient with Hindsight Observability.
ICML
Jonathan Lee, Alekh Agarwal, Christoph Dann, Tong Zhang
2023 A* conf
Supervised Pretraining Can Learn In-Context Reinforcement Learning.
NeurIPS
Jonathan Lee, Annie Xie, Aldo Pacchiano, Yash Chandak, Chelsea Finn, Ofir Nachum, Emma Brunskill
2022 A* conf
Model Selection in Batch Policy Optimization.
ICML
Jonathan Lee, George Tucker, Ofir Nachum, Bo Dai
2021 J jnl
Dueling RL: Reinforcement Learning with Trajectory Preferences.
CoRR
Aldo Pacchiano, Aadirupa Saha, Jonathan Lee
2021 J jnl
Sequential robot imitation learning from observations.
Int. J. Robotics Res.
Ajay Kumar Tanwani, Andy Yan, Jonathan Lee, Sylvain Calinon, Ken Goldberg
2020 A conf
Online Learning with Continuous Variations: Dynamic Regret and Reductions.
AISTATS
Ching-An Cheng, Jonathan Lee, Ken Goldberg, Byron Boots
2019 J jnl
Continuous Online Learning and New Insights to Online Imitation Learning.
CoRR
Jonathan Lee, Ching-An Cheng, Ken Goldberg, Byron Boots
2019 Misc conf
On-Policy Robot Imitation Learning from a Converging Supervisor.
CoRL
Ashwin Balakrishna, Brijen Thananjeyan, Jonathan Lee, Felix Li, Arsh Zahed, Joseph E. Gonzalez, Ken Goldberg
2019 J jnl
On-Policy Robot Imitation Learning from a Converging Supervisor.
CoRR
Ashwin Balakrishna, Brijen Thananjeyan, Jonathan Lee, Arsh Zahed, Felix Li, Joseph E. Gonzalez, Ken Goldberg
2019 J jnl
Online Learning with Continuous Variations: Dynamic Regret and Reductions.
CoRR
Ching-An Cheng, Jonathan Lee, Ken Goldberg, Byron Boots
2018 J jnl
A Dynamic Regret Analysis and Adaptive Regularization Algorithm for On-Policy Robot Imitation Learning.
CoRR
Jonathan Lee, Michael Laskey, Ajay Kumar Tanwani, Anil Aswani, Ken Goldberg
2018 — conf
Constraint Estimation and Derivative-Free Recovery for Robot Learning from Demonstrations.
CASE
Jonathan Lee, Michael Laskey, Roy Fox, Ken Goldberg
2018 J jnl
Derivative-Free Failure Avoidance Control for Manipulation using Learned Support Constraints.
CoRR
Jonathan Lee, Michael Laskey, Roy Fox, Ken Goldberg
2018 C conf
Generalizing Robot Imitation Learning with Invariant Hidden Semi-Markov Models.
WAFR
Ajay Kumar Tanwani, Jonathan Lee, Brijen Thananjeyan, Michael Laskey, Sanjay Krishnan, Roy Fox, Ken Goldberg, Sylvain Calinon
2018 J jnl
Generalizing Robot Imitation Learning with Invariant Hidden Semi-Markov Models.
CoRR
Ajay Kumar Tanwani, Jonathan Lee, Brijen Thananjeyan, Michael Laskey, Sanjay Krishnan, Roy Fox, Ken Goldberg, Sylvain Calinon
2018 — conf
Malasakit 2.0: A Participatory Online Platform with Feature Phone Integration and Voice Recognition for Crowdsourcing Disaster Risk Reduction Strategies in the Philippines.
GHTC
Brandie Nonnecke, Shrestha Mohanty, Andrew Lee, Jonathan Lee, Sequoia Beckman, Justin Mi, Thanatcha Panpairoj, Jeffrey Rosario Ancheta, Hilary Martinez, Nathaniel Oco, Rachel Edita Roxas, Camille Crittenden, Ken Goldberg
2017 A* conf
Comparing human-centric and robot-centric sampling for robot deep learning from demonstrations.
ICRA
Michael Laskey, Caleb Chuck, Jonathan Lee, Jeffrey Mahler, Sanjay Krishnan, Kevin Jamieson, Anca D. Dragan, Ken Goldberg
2017 Misc conf
DART: Noise Injection for Robust Imitation Learning.
CoRL
Michael Laskey, Jonathan Lee, Roy Fox, Anca D. Dragan, Ken Goldberg
2017 J jnl
Iterative Noise Injection for Scalable Imitation Learning.
CoRR
Michael Laskey, Jonathan Lee, Wesley Yu-Shu Hsieh, Richard Liaw, Jeffrey Mahler, Roy Fox, Ken Goldberg
2017 — conf
Malasakit 1.0: A participatory online platform for crowdsourcing disaster risk reduction strategies in the philippines.
GHTC
Brandie Nonnecke, Shrestha Mohanty, Andrew Lee, Jonathan Lee, Sequoia Beckman, Justin Mi, Sanjay Krishnan, Rachel Edita Roxas, Nathaniel Oco, Camille Crittenden, Ken Goldberg
2016 J jnl
Comparing Human-Centric and Robot-Centric Sampling for Robot Deep Learning from Demonstrations.
CoRR
Michael Laskey, Caleb Chuck, Jonathan Lee, Jeffrey Mahler, Sanjay Krishnan, Kevin Jamieson, Anca D. Dragan, Kenneth Y. Goldberg
2016 — conf
Robot grasping in clutter: Using a hierarchy of supervisors for learning from demonstrations.
CASE
Michael Laskey, Jonathan Lee, Caleb Chuck, David V. Gealy, Wesley Yu-Shu Hsieh, Florian T. Pokorny, Anca D. Dragan, Ken Goldberg