I am a PhD Candidate in Computing + Mathematical Sciences at Caltech. I do machine learning with Professor Yisong Yue.

I’m interested in sequential decision problems: specifically, how to efficiently integrate domain knowledge and structure into data-driven methods . My research overlaps with reinforcement learning, imitation learning and optimal control.

I’m fortunate to spend previous two summers at Microsoft Research in NYC and Disney Research in Pittsburgh. I’m currently supported by an Amazon AI Graduate fellowship.

News & Announcements

• I gave a tutorial on Imitation Learning, together with Professor Yisong Yue at the International Conference on Machine Learning (ICML) in Stockholm in July 2018
• I'm TA-ing an advanced topics course at Caltech with a special focus on reinforcement learning

Preprints

• Hoang M. Le, Cameron Voloshin and Yisong Yue
  Batch Policy Learning under Constraints
  (under review) , 2019
  [PDF] [Project Page] [BibTeX]

  @article{le2019batch,
    title={Batch Policy Learning under Constraints},
    author={Le, Hoang M and Voloshin, Cameron and Yue, Yisong},
    journal={arXiv preprint arXiv:1903.08738},
    year={2019}
  }
  

• Andrew J. Taylor, Victor D. Dorobantu, Meera Krisnamoorthy, Hoang M. Le, Yisong Yue and Aaron D. Ames
  A Control Lyapunov Perspective on Episodic Learning via Projection to State Stability
  (under review) , 2019
  [PDF] [BibTeX]

  @article{taylor2019acontrol,
    title={A Control Lyapunov Perspective on Episodic Learning via Projection to State Stability},
    author={Taylor, Andrew J and Dorobantu, Victor D and Krisnamoorthy, Meera and Le, Hoang M and Yue, Yisong and Ames, Aaron D},
    journal={arXiv preprint arXiv:1903.07214},
    year={2019}
  }
  

• Andrew J. Taylor, Victor D. Dorobantu, Hoang M. Le, Yisong Yue and Aaron D. Ames
  Episodic Learning with Control Lyapunov Functions for Uncertain Robotic Systems
  (under review) , 2019
  [PDF][code] [BibTeX]

  @article{taylor2019episodic,
    title={Episodic Learning with Control Lyapunov Functions for Uncertain Robotic Systems},
    author={Taylor, Andrew J and Dorobantu, Victor D and Le, Hoang M and Yue, Yisong and Ames, Aaron D},
    journal={arXiv preprint arXiv:1903.01577},
    year={2019}
  }
  

Representative Publications

• Hoang M. Le, Nan Jiang, Alekh Agarwal, Miroslav Dudík, Yisong Yue and Hal Daumé III
  Hierarchical Imitation and Reinforcement Learning
  International Conference on Machine Learning (ICML), 2018
  [PDF] [Project Page] [BibTeX]

  @inproceedings{le2018hierarchical,
    title={Hierarchical Imitation and Reinforcement Learning},
    author={Le, Hoang and Jiang, Nan and Agarwal, Alekh and Dudik, Miroslav and Yue, Yisong and Daum{\'e}, Hal},
    booktitle={International Conference on Machine Learning},
    pages={2923--2932},
    year={2018}
  }
  

• Hoang M. Le, Yisong Yue, Peter Carr and Patrick Lucey
  Coordinated Multi-Agent Imitation Learning
  International Conference on Machine Learning (ICML), 2017
  [PDF] [long] [BibTeX]

  @inproceedings{le2017coordinated,
    title={Coordinated Multi-Agent Imitation Learning},
    author={Le, Hoang M and Yue, Yisong and Carr, Peter and Lucey, Patrick},
    booktitle={International Conference on Machine Learning},
    pages={1995--2003},
    year={2017}
  }
  

• Hoang M. Le, Peter Carr,Yisong Yue and Patrick Lucey
  Data-Driven Ghosting using Deep Imitation Learning
  MIT Sloan Sports Analytics Conference (SSAC), 2017
  (Best Paper Runner-Up Award)
  [PDF] [Project Page] [Video Demo] [BibTeX]

  @article{le2017data,
    title={Data-Driven Ghosting using Deep Imitation Learning},
    author={Le, Hoang M and Carr, Peter and Yue, Yisong and Lucey, Patrick}
    journal={MIT Sloan Sports Analytics Conference (SSAC)},
    year={2017}
  }
  

• Hoang M. Le, Andrew Kang, Yisong Yue and Peter Carr
  Smooth Imitation Learning for Online Sequence Prediction
  International Conference on Machine Learning (ICML), 2016
  [PDF] [long] [BibTeX]

  @inproceedings{le2016smooth,
    title={Smooth Imitation Learning for Online Sequence Prediction},
    author={Le, Hoang and Kang, Andrew and Yue, Yisong and Carr, Peter},
    booktitle={International Conference on Machine Learning},
    pages={680--688},
    year={2016}
  }

• Jianhui Chen, Hoang M. Le, Peter Carr, Yisong Yue and James J. Little
  Learning Online Smooth Predictors for Real-time Camera Planning using Recurrent Decision Trees
  Computer Vision and Pattern Recognition (CVPR), 2016
  (Oral Presentation)
  [PDF] [Press Release] [BibTeX]

  @inproceedings{chen2016learning,
    title={Learning online smooth predictors for realtime camera planning using recurrent decision trees},
    author={Chen, Jianhui and Le, Hoang M and Carr, Peter and Yue, Yisong and Little, James J},
    booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
    pages={4688--4696},
    year={2016}
  }

Pending Patents

• George Peter Kenneth Carr, Hoang M. Le, Yisong Yue
  Data-Driven Ghosting Using Deep Imitation Learning
  [patent pending]