Resultats de la cerca - Ganesh, Arun

Tight Group-Level DP Guarantees for DP-SGD with Sampling via Mixture of Gaussians Mechanisms per Ganesh, Arun

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Tighter Privacy Analysis for Truncated Poisson Sampling per Ganesh, Arun

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Near-Linear Time Edit Distance for Indel Channels per Ganesh, Arun, Sy, Aaron

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Privately Answering Counting Queries with Generalized Gaussian Mechanisms per Ganesh, Arun, Zhao, Jiazheng

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Faster Differentially Private Samplers via Rényi Divergence Analysis of Discretized Langevin MCMC per Ganesh, Arun, Talwar, Kunal

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Privacy Amplification for BandMF via $b$-Min-Sep Subsampling per Dong, Andy, Ganesh, Arun

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Better Batches, Better Privacy: Random Allocation for DP-BandMF per McKenna, Ryan, Ganesh, Arun

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Differentially Private Sampling from Rashomon Sets, and the Universality of Langevin Diffusion for Convex Optimization per Ganesh, Arun, Thakurta, Abhradeep, Upadhyay, Jalaj

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Robust Algorithms for TSP and Steiner Tree per Ganesh, Arun, Maggs, Bruce M., Panigrahi, Debmalya

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Universal Algorithms for Clustering Problems per Ganesh, Arun, Maggs, Bruce M., Panigrahi, Debmalya

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On Design Principles for Private Adaptive Optimizers per Ganesh, Arun, McMahan, Brendan, Thakurta, Abhradeep

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How Compression and Approximation Affect Efficiency in String Distance Measures per Ganesh, Arun, Kociumaka, Tomasz, Lincoln, Andrea, Saha, Barna

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Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks per Ganesh, Arun, Liu, Daogao, Oh, Sewoong, Thakurta, Abhradeep

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Faster Differentially Private Convex Optimization via Second-Order Methods per Ganesh, Arun, Haghifam, Mahdi, Steinke, Thomas, Thakurta, Abhradeep

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Optimal Rates for $O(1)$-Smooth DP-SCO with a Single Epoch and Large Batches per Choquette-Choo, Christopher A., Ganesh, Arun, Thakurta, Abhradeep

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Privacy Amplification for Matrix Mechanisms per Choquette-Choo, Christopher A., Ganesh, Arun, Steinke, Thomas, Thakurta, Abhradeep

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Hush! Protecting Secrets During Model Training: An Indistinguishability Approach per Ganesh, Arun, McMahan, Brendan, Nasr, Milad, Steinke, Thomas, Thakurta, Abhradeep

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Advancing the State-of-the-Art in Empirical Privacy Auditing per Mitchell, Nicole, Andrew, Galen, Ganesh, Arun, McMahan, Brendan, Kairouz, Peter

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Near Exact Privacy Amplification for Matrix Mechanisms per Choquette-Choo, Christopher A., Ganesh, Arun, Haque, Saminul, Steinke, Thomas, Thakurta, Abhradeep

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It's My Data Too: Private ML for Datasets with Multi-User Training Examples per Ganesh, Arun, McKenna, Ryan, McMahan, Brendan, Smith, Adam, Wu, Fan

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