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Mixed Differential Privacy in Computer Vision



Aditya Golatkar , Alessandro Achille , Yu-Xiang Wang , Aaron Roth , Michael Kearns , Stefano Soatto

* Accepted at CVPR 2022 

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Beyond the Frontier: Fairness Without Accuracy Loss



Ira Globus-Harris , Michael Kearns , Aaron Roth


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Beyond the Frontier: Fairness Without Privacy Loss



Ira Globus-Harris , Michael Kearns , Aaron Roth


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Online Multiobjective Minimax Optimization and Applications



Georgy Noarov , Mallesh Pai , Aaron Roth


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Multiaccurate Proxies for Downstream Fairness



Emily Diana , Wesley Gill , Michael Kearns , Krishnaram Kenthapadi , Aaron Roth , Saeed Sharifi-Malvajerdi


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Adaptive Machine Unlearning



Varun Gupta , Christopher Jung , Seth Neel , Aaron Roth , Saeed Sharifi-Malvajerdi , Chris Waites


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Rejoinder: Gaussian Differential Privacy



Jinshuo Dong , Aaron Roth , Weijie J. Su

* Rejoinder to discussions on Gaussian Differential Privacy, read to the Royal Statistical Society in December 2020 

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Differentially Private Query Release Through Adaptive Projection



Sergul Aydore , William Brown , Michael Kearns , Krishnaram Kenthapadi , Luca Melis , Aaron Roth , Ankit Siva


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Lexicographically Fair Learning: Algorithms and Generalization



Emily Diana , Wesley Gill , Ira Globus-Harris , Michael Kearns , Aaron Roth , Saeed Sharifi-Malvajerdi


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Online Multivalid Learning: Means, Moments, and Prediction Intervals



Varun Gupta , Christopher Jung , Georgy Noarov , Mallesh M. Pai , Aaron Roth


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