80 citations · 167 across the 23 of their papers we have counts for
8 papers · 1 filter
Multi-Task Learning with Sequence-Conditioned Transporter Networks
Michael H. Lim, Andy Zeng, Brian Ichter +5
Enabling robots to solve multiple manipulation tasks has a wide range of industrial applications. While learning-based approaches enjoy flexibility and generalizability, scaling th…
Voronoi Progressive Widening: Efficient Online Solvers for Continuous State, Action, and Observation POMDPs
Michael H. Lim, Claire J. Tomlin, Zachary N. Sunberg
This paper introduces Voronoi Progressive Widening (VPW), a generalization of Voronoi optimistic optimization (VOO) and action progressive widening to partially observable Markov d…
Testing for Typicality with Respect to an Ensemble of Learned Distributions
Forrest Laine, Claire Tomlin
Methods of performing anomaly detection on high-dimensional data sets are needed, since algorithms which are trained on data are only expected to perform well on data that is simil…
Expert Selection in High-Dimensional Markov Decision Processes
Vicenc Rubies-Royo, Eric Mazumdar, Roy Dong +2
In this work we present a multi-armed bandit framework for online expert selection in Markov decision processes and demonstrate its use in high-dimensional settings. Our method tak…
Dynamically Computing Adversarial Perturbations for Recurrent Neural Networks
Shankar A. Deka, Dušan M. Stipanović, Claire J. Tomlin
Convolutional and recurrent neural networks have been widely employed to achieve state-of-the-art performance on classification tasks. However, it has also been noted that these ne…
A Successive-Elimination Approach to Adaptive Robotic Sensing
Esther Rolf, David Fridovich-Keil, Max Simchowitz +2
We study an adaptive source seeking problem, in which a mobile robot must identify the strongest emitter(s) of a signal in an environment with background emissions. Background sign…