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Causal Feature Discovery through Strategic Modification

Feb 17, 2020
Yahav Bechavod, Katrina Ligett, Zhiwei Steven Wu, Juba Ziani


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Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization

Feb 13, 2020
Vikas K. Garg, Adam Kalai, Katrina Ligett, Zhiwei Steven Wu


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Privately Learning Thresholds: Closing the Exponential Gap

Nov 22, 2019
Haim Kaplan, Katrina Ligett, Yishay Mansour, Moni Naor, Uri Stemmer


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A New Analysis of Differential Privacy's Generalization Guarantees

Sep 09, 2019
Christopher Jung, Katrina Ligett, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, Moshe Shenfeld


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A necessary and sufficient stability notion for adaptive generalization

Jun 03, 2019
Katrina Ligett, Moshe Shenfeld


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Learning to Prune: Speeding up Repeated Computations

Apr 26, 2019
Daniel Alabi, Adam Tauman Kalai, Katrina Ligett, Cameron Musco, Christos Tzamos, Ellen Vitercik


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Equal Opportunity in Online Classification with Partial Feedback

Feb 06, 2019
Yahav Bechavod, Katrina Ligett, Aaron Roth, Bo Waggoner, Zhiwei Steven Wu

* 28 pages 

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Penalizing Unfairness in Binary Classification

Mar 08, 2018
Yahav Bechavod, Katrina Ligett


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Accuracy First: Selecting a Differential Privacy Level for Accuracy-Constrained ERM

May 30, 2017
Katrina Ligett, Seth Neel, Aaron Roth, Bo Waggoner, Z. Steven Wu

* 24 pages single-column 

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Adaptive Learning with Robust Generalization Guarantees

Jun 02, 2016
Rachel Cummings, Katrina Ligett, Kobbi Nissim, Aaron Roth, Zhiwei Steven Wu


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Truthful Linear Regression

Jun 10, 2015
Rachel Cummings, Stratis Ioannidis, Katrina Ligett

* To appear in Proceedings of the 28th Annual Conference on Learning Theory (COLT 2015) 

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A Learning Theory Approach to Non-Interactive Database Privacy

Sep 10, 2011
Avrim Blum, Katrina Ligett, Aaron Roth

* Full Version. Extended Abstract appeared in STOC 2008 

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Differential Privacy with Compression

Jan 10, 2009
Shuheng Zhou, Katrina Ligett, Larry Wasserman

* 14 pages 

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