296 citations · 530 across the 29 of their papers we have counts for
31 papers
Efficiency in Collective Decision-Making via Quadratic Transfers
Jon X. Eguia, Nicole Immorlica, Steven P. Lalley +3
Consider the following collective choice problem: a group of budget constrained agents must choose one of several alternatives. Is there a budget balanced mechanism that: i) does n…
Generalization in the Face of Adaptivity: A Bayesian Perspective
Moshe Shenfeld, Katrina Ligett
Repeated use of a data sample via adaptively chosen queries can rapidly lead to overfitting, wherein the empirical evaluation of queries on the sample significantly deviates from t…
Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization
Vikas K. Garg, Adam Kalai, Katrina Ligett +1
Domain generalization is the problem of machine learning when the training data and the test data come from different data domains. We present a simple theoretical model of learnin…
Gaming Helps! Learning from Strategic Interactions in Natural Dynamics
Yahav Bechavod, Katrina Ligett, Zhiwei Steven Wu +1
We consider an online regression setting in which individuals adapt to the regression model: arriving individuals are aware of the current model, and invest strategically in modify…
Privately Learning Thresholds: Closing the Exponential Gap
Haim Kaplan, Katrina Ligett, Yishay Mansour +2
We study the sample complexity of learning threshold functions under the constraint of differential privacy. It is assumed that each labeled example in the training data is the inf…
A New Analysis of Differential Privacy's Generalization Guarantees
Christopher Jung, Katrina Ligett, Seth Neel +3
We give a new proof of the "transfer theorem" underlying adaptive data analysis: that any mechanism for answering adaptively chosen statistical queries that is differentially priva…