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Ravi Kumar

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Training Differentially Private Ad Prediction Models with Semi-Sensitive Features

Jan 26, 2024
Lynn Chua, Qiliang Cui, Badih Ghazi, Charlie Harrison, Pritish Kamath, Walid Krichene, Ravi Kumar, Pasin Manurangsi, Krishna Giri Narra, Amer Sinha, Avinash Varadarajan, Chiyuan Zhang

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Optimal Unbiased Randomizers for Regression with Label Differential Privacy

Dec 09, 2023
Ashwinkumar Badanidiyuru, Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V Varadarajan, Chiyuan Zhang

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Sparsity-Preserving Differentially Private Training of Large Embedding Models

Nov 14, 2023
Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang

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User-Level Differential Privacy With Few Examples Per User

Sep 21, 2023
Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang

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Ticketed Learning-Unlearning Schemes

Jun 27, 2023
Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Ayush Sekhari, Chiyuan Zhang

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Approximating a RUM from Distributions on k-Slates

May 22, 2023
Flavio Chierichetti, Mirko Giacchini, Ravi Kumar, Alessandro Panconesi, Andrew Tomkins

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On User-Level Private Convex Optimization

May 08, 2023
Badih Ghazi, Pritish Kamath, Ravi Kumar, Raghu Meka, Pasin Manurangsi, Chiyuan Zhang

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Revenue Management without Demand Forecasting: A Data-Driven Approach for Bid Price Generation

Apr 14, 2023
Ezgi C. Eren, Zhaoyang Zhang, Jonas Rauch, Ravi Kumar, Royce Kallesen

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Regression with Label Differential Privacy

Dec 12, 2022
Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash Varadarajan, Chiyuan Zhang

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Private Ad Modeling with DP-SGD

Nov 21, 2022
Carson Denison, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Krishna Giri Narra, Amer Sinha, Avinash Varadarajan, Chiyuan Zhang

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