activity
20112020
most citedEfficient Optimal Learning for Contextual Bandits

119 citations · 128 across the 5 of their papers we have counts for

collaborators

6 papers

cs.LG20207 cited

Statistical Queries and Statistical Algorithms: Foundations and Applications

Lev Reyzin

We give a survey of the foundations of statistical queries and their many applications to other areas. We introduce the model, give the main definitions, and we explore the fundame…

cs.LG2020

On the Complexity of Learning from Label Proportions

Benjamin Fish, Lev Reyzin

In the problem of learning with label proportions, which we call LLP learning, the training data is unlabeled, and only the proportions of examples receiving each label are given.…

cs.LG2020

On Biased Random Walks, Corrupted Intervals, and Learning Under Adversarial Design

Daniel Berend, Aryeh Kontorovich, Lev Reyzin +1

We tackle some fundamental problems in probability theory on corrupted random processes on the integer line. We analyze when a biased random walk is expected to reach its bottommos…

cs.LG20192 cited

Crowdsourced PAC Learning under Classification Noise

Shelby Heinecke, Lev Reyzin

In this paper, we analyze PAC learnability from labels produced by crowdsourcing. In our setting, unlabeled examples are drawn from a distribution and labels are crowdsourced from…

cs.DS2017

Network Construction with Ordered Constraints

Yi Huang, Mano Vikash Janardhanan, Lev Reyzin

In this paper, we study the problem of constructing a network by observing ordered connectivity constraints, which we define herein. These ordered constraints are made to capture r…

cs.LG2011119 cited

Efficient Optimal Learning for Contextual Bandits

Miroslav Dudik, Daniel Hsu, Satyen Kale +4

We address the problem of learning in an online setting where the learner repeatedly observes features, selects among a set of actions, and receives reward for the action taken. We…