29 citations · 65 across the 13 of their papers we have counts for
3 papers · 1 filter
PAC Reinforcement Learning without Real-World Feedback
Yuren Zhong, Aniket Anand Deshmukh, Clayton Scott
This work studies reinforcement learning in the Sim-to-Real setting, in which an agent is first trained on a number of simulators before being deployed in the real world, with the…
Learning from Multiple Corrupted Sources, with Application to Learning from Label Proportions
Clayton Scott, Jianxin Zhang
We study binary classification in the setting where the learner is presented with multiple corrupted training samples, with possibly different sample sizes and degrees of corruptio…
A Generalization Error Bound for Multi-class Domain Generalization
Aniket Anand Deshmukh, Yunwen Lei, Srinagesh Sharma +3
Domain generalization is the problem of assigning labels to an unlabeled data set, given several similar data sets for which labels have been provided. Despite considerable interes…