239 citations · 399 across the 20 of their papers we have counts for
33 papers
Optimal Exploration for Model-Based RL in Nonlinear Systems
Andrew Wagenmaker, Guanya Shi, Kevin Jamieson
Learning to control unknown nonlinear dynamical systems is a fundamental problem in reinforcement learning and control theory. A commonly applied approach is to first explore the e…
Active Representation Learning for General Task Space with Applications in Robotics
Yifang Chen, Yingbing Huang, Simon S. Du +2
Representation learning based on multi-task pretraining has become a powerful approach in many domains. In particular, task-aware representation learning aims to learn an optimal r…
Active Multi-Task Representation Learning
Yifang Chen, Simon S. Du, Kevin Jamieson
To leverage the power of big data from source tasks and overcome the scarcity of the target task samples, representation learning based on multi-task pretraining has become a stand…
Practical, Provably-Correct Interactive Learning in the Realizable Setting: The Power of True Believers
Julian Katz-Samuels, Blake Mason, Kevin Jamieson +1
We consider interactive learning in the realizable setting and develop a general framework to handle problems ranging from best arm identification to active classification. We begi…
Nearly Optimal Algorithms for Level Set Estimation
Blake Mason, Romain Camilleri, Subhojyoti Mukherjee +3
The level set estimation problem seeks to find all points in a domain where the value of an unknown function exceeds a threshold .…
Selective Sampling for Online Best-arm Identification
Romain Camilleri, Zhihan Xiong, Maryam Fazel +2
This work considers the problem of selective-sampling for best-arm identification. Given a set of potential options , a learner aims to compute with…