activity
20172020
most citedUnsupervised Learning for Nonlinear PieceWise Smooth Hybrid Systems

8 citations · 11 across the 3 of their papers we have counts for

collaborators

10 papers

cs.RO2020

Posterior Sampling for Anytime Motion Planning on Graphs with Expensive-to-Evaluate Edges

Brian Hou, Sanjiban Choudhury, Gilwoo Lee +2

Collision checking is a computational bottleneck in motion planning, requiring lazy algorithms that explicitly reason about when to perform this computation. Optimism in the face o…

cs.RO2020

Bayesian Residual Policy Optimization: Scalable Bayesian Reinforcement Learning with Clairvoyant Experts

Gilwoo Lee, Brian Hou, Sanjiban Choudhury +1

Informed and robust decision making in the face of uncertainty is critical for robots that perform physical tasks alongside people. We formulate this as Bayesian Reinforcement Lear…

cs.RO2019

Towards Effective Human-AI Teams: The Case of Collaborative Packing

Gilwoo Lee, Christoforos Mavrogiannis, Siddhartha S. Srinivasa

We focus on the problem of designing an artificial agent (AI), capable of assisting a human user to complete a task. Our goal is to guide human users towards optimal task performan…

cs.RO2019

Robot-Assisted Feeding: Generalizing Skewering Strategies across Food Items on a Realistic Plate

Ryan Feng, Youngsun Kim, Gilwoo Lee +5

A robot-assisted feeding system must successfully acquire many different food items. A key challenge is the wide variation in the physical properties of food, demanding diverse acq…

cs.LG2019

Imitation Learning as -Divergence Minimization

Liyiming Ke, Sanjiban Choudhury, Matt Barnes +3

We address the problem of imitation learning with multi-modal demonstrations. Instead of attempting to learn all modes, we argue that in many tasks it is sufficient to imitate any…

cs.LG2018

Bayes-CPACE: PAC Optimal Exploration in Continuous Space Bayes-Adaptive Markov Decision Processes

Gilwoo Lee, Sanjiban Choudhury, Brian Hou +1

We present the first PAC optimal algorithm for Bayes-Adaptive Markov Decision Processes (BAMDPs) in continuous state and action spaces, to the best of our knowledge. The BAMDP fram…