Publications
Bayesian Residual Policy Optimization: Scalable Bayesian Reinforcement Learning with Clairvoyant Experts
Gilwoo Lee, Brian Hou, Sanjiban Choudhury, Siddhartha S. Srinivasa.
IROS, 2021.
Posterior Sampling for Anytime Motion Planning on Graphs with Expensive-to-Evaluate Edges
Brian Hou, Sanjiban Choudhury, Gilwoo Lee, Aditya Mandalika, Siddhartha S. Srinivasa.
ICRA, 2020.
Bayesian Policy Optimization for Model Uncertainty
Gilwoo Lee, Brian Hou, Aditya Mandalika, Jeongseok Lee, Sanjiban Choudhury, Siddhartha S. Srinivasa.
ICLR, 2019.
Efficient Motion Planning for Problems Lacking Optimal Substructure
Oren Salzman, Brian Hou, Siddhartha S. Srinivasa.
ICAPS, 2017.
Privacy-Preserving Cloud-Based Grasp Planning
Jeffrey Mahler, Brian Hou, Sherdil Niyaz, Florian T. Pokorny, Ramu Chandra, Ken Goldberg.
CASE, 2016.
Dex-Net 1.0: A Cloud-Based Network of 3D Objects for Robust Grasp Planning Using a Multi-Armed Bandit Model with Correlated Rewards
Jeffrey Mahler, Florian T. Pokorny, Brian Hou, Melrose Roderick, Michael Laskey, Mathieu Aubry, Kai Kohlhoff, Torsten Kroeger, James Kuffner, Ken Goldberg.
ICRA, 2016.
Fuzz Testing Projects in Massive Courses
Sumukh Sridhara, Brian Hou, Jeffrey Lu, John DeNero.
Learning at Scale, 2016.
Restaurant Recommendations
Brian Hou, Marvin Zhang, John DeNero.
SIGCSE Nifty Assignments, 2016.
Problems Before Solutions: Automated Problem Clarification at Scale.
Soumya Basu, Albert Wu, Brian Hou, John DeNero.
Learning at Scale, 2015.