Publications

2023

  1. ICML
    The Virtues of Laziness in Model-based RL: A Unified Objective and Algorithms
    Vemula, Anirudh, Song, Yuda, Singh, Aarti, Bagnell, J Andrew, and Choudhury, Sanjiban
    In 2023
    PDF
  2. ICML
    Inverse Reinforcement Learning without Reinforcement Learning
    Swamy, Gokul, Choudhury, Sanjiban, Bagnell, J Andrew, and Wu, Zhiwei Steven
    In 2023
    PDF
  3. ICML
    The Virtues of Laziness in Model-based RL: A Unified Objective and Algorithms
    Vemula, Anirudh, Song, Yuda, Singh, Aarti, Bagnell, J Andrew, and Choudhury, Sanjiban
    In 2023
    PDF
  4. ICRA
    Guided Incremental Local Densification for Accelerated Sampling-based Motion Planning
    Mandalika, Aditya, Scalise, Rosario, Hou, Brian, Choudhury, Sanjiban, and Srinivasa, Siddhartha S.
    In IEEE International Conference on Robotics and Automation 2023
    PDF
  5. ICLR
    Impossibly Good Experts and How to Follow Them
    Walsman, Aaron, Zhang, Muru, Choudhury, Sanjiban, Fox, Dieter, and Farhadi, Ali
    In International Conference on Learning Representations 2023
    PDF
  6. ICRA
    Guided Incremental Local Densification for Accelerated Sampling-based Motion Planning
    Mandalika, Aditya, Scalise, Rosario, Hou, Brian, Choudhury, Sanjiban, and Srinivasa, Siddhartha S.
    In IEEE International Conference on Robotics and Automation 2023
    PDF

2022

  1. NeurIPS
    Minimax Optimal Online Imitation Learning via Replay Estimation
    Swamy, Gokul, Rajaraman, Nived, Peng, Matthew, Choudhury, Sanjiban, Bagnell, J Andrew, Wu, Zhiwei Steven, Jiao, Jiantao, and Ramchandran, Kannan
    In Advances in Neural Information Processing Systems 2022
    PDF
  2. NeurIPS
    Minimax Optimal Online Imitation Learning via Replay Estimation
    Swamy, Gokul, Rajaraman, Nived, Peng, Matthew, Choudhury, Sanjiban, Bagnell, J Andrew, Wu, Zhiwei Steven, Jiao, Jiantao, and Ramchandran, Kannan
    In Advances in Neural Information Processing Systems 2022
    PDF
  3. NeurIPS
    Sequence Model Imitation Learning with Unobserved Contexts
    Swamy, Gokul, Choudhury, Sanjiban, Bagnell, J Andrew, and Wu, Zhiwei Steven
    In Advances in Neural Information Processing Systems 2022
    PDF
  4. ICML
    Causal imitation learning under temporally correlated noise
    Swamy, Gokul, Choudhury, Sanjiban, Bagnell, Drew, and Wu, Steven
    In International Conference on Machine Learning 2022
    PDF
  5. ICML
    Towards Uniformly Superhuman Autonomy via Subdominance Minimization
    Ziebart, Brian, Choudhury, Sanjiban, Yan, Xinyan, and Vernaza, Paul
    In International Conference on Machine Learning 2022
  6. ICML
    Causal Imitation Learning under Temporally Correlated Noise
    Swamy, Gokul, Choudhury, Sanjiban, Bagnell, J. Andrew, and Wu, Zhiwei Steven
    In International Conference on Machine Learning 2022
    PDF

2021

  1. AuRo
    Expert Intervention Learning
    Spencer, Jonathan, Choudhury, Sanjiban, Barnes, Matthew, Schmittle, Matthew, Chiang, Mung, Ramadge, Peter, and Srinivasa, Sidd
    Autonomous Robots 2021
    PDF
  2. arXiv
    Feedback in Imitation Learning: The Three Regimes of Covariate Shift
    Spencer, Jonathan, Choudhury, Sanjiban, Venkatraman, Arun, Ziebart, Brian, and Bagnell, J Andrew
    arXiv preprint arXiv:2102.02872 2021
    PDF
  3. ICML
    Of Moments and Matching: A Game-Theoretic Framework for Closing the Imitation Gap
    Swamy, Gokul, Choudhury, Sanjiban, Bagnell, J. Andrew, and Wu, Steven
    In International Conference on Machine Learning 2021
    PDF
  4. ICLR
    Blending mpc & value function approximation for efficient reinforcement learning
    Bhardwaj, Mohak, Choudhury, Sanjiban, and Boots, Byron
    2021
    PDF
  5. IROS
    Bayesian Residual Policy Optimization: Scalable Bayesian Reinforcement Learning with Clairvoyant Experts
    Lee, G., Hou, B., Choudhury, S., and Srinivasa, S.S
    2021
    PDF

2020

  1. RSS
    Learning from Interventions: Human-robot interaction as both explicit and implicit feedback
    Spencer, J., Choudhury, S., Barnes, M., and Srinivasa, S.
    In Robotics: Science and Systems 2020
    PDF
  2. WAFR
    Imitation Learning as f-Divergence Minimization
    Ke, L., Choudhury, S., Barnes, M., Sun, W., Lee, G., and Srinivasa, S.
    In Workshop on the Algorithmic Foundations of Robotics 2020
    PDF