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Krishna Pillutla

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Distributionally Robust Optimization with Bias and Variance Reduction

Oct 21, 2023
Ronak Mehta, Vincent Roulet, Krishna Pillutla, Zaid Harchaoui

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User Inference Attacks on Large Language Models

Oct 13, 2023
Nikhil Kandpal, Krishna Pillutla, Alina Oprea, Peter Kairouz, Christopher A. Choquette-Choo, Zheng Xu

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Correlated Noise Provably Beats Independent Noise for Differentially Private Learning

Oct 10, 2023
Christopher A. Choquette-Choo, Krishnamurthy Dvijotham, Krishna Pillutla, Arun Ganesh, Thomas Steinke, Abhradeep Thakurta

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Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning

Jul 18, 2023
Zachary Charles, Nicole Mitchell, Krishna Pillutla, Michael Reneer, Zachary Garrett

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Unleashing the Power of Randomization in Auditing Differentially Private ML

May 29, 2023
Krishna Pillutla, Galen Andrew, Peter Kairouz, H. Brendan McMahan, Alina Oprea, Sewoong Oh

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Modified Gauss-Newton Algorithms under Noise

May 18, 2023
Krishna Pillutla, Vincent Roulet, Sham Kakade, Zaid Harchaoui

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MAUVE Scores for Generative Models: Theory and Practice

Dec 30, 2022
Krishna Pillutla, Lang Liu, John Thickstun, Sean Welleck, Swabha Swayamdipta, Rowan Zellers, Sewoong Oh, Yejin Choi, Zaid Harchaoui

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Stochastic Optimization for Spectral Risk Measures

Dec 10, 2022
Ronak Mehta, Vincent Roulet, Krishna Pillutla, Lang Liu, Zaid Harchaoui

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Statistical and Computational Guarantees for Influence Diagnostics

Dec 08, 2022
Jillian Fisher, Lang Liu, Krishna Pillutla, Yejin Choi, Zaid Harchaoui

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Federated Learning with Partial Model Personalization

Apr 08, 2022
Krishna Pillutla, Kshitiz Malik, Abdelrahman Mohamed, Michael Rabbat, Maziar Sanjabi, Lin Xiao

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