Arun Ganesh

55 papers A* 17B 1C 1Journal 33Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
JAX-Privacy: A library for differentially private machine learning.
CoRR
Ryan McKenna, Galen Andrew, Borja Balle, Vadym Doroshenko, Arun Ganesh, Weiwei Kong, Alex Kurakin, Brendan McMahan, Mikhail Pravilov
2026 J jnl
Privacy Amplification for BandMF via
CoRR
Andy Dong, Arun Ganesh
2025 J jnl
Correlated Noise Mechanisms for Differentially Private Learning.
CoRR
Krishna Pillutla, Jalaj Upadhyay, Christopher A. Choquette-Choo, Krishnamurthy Dvijotham, Arun Ganesh, Monika Henzinger, Jonathan Katz, Ryan McKenna, H. Brendan McMahan, Keith Rush, Thomas Steinke, Abhradeep Thakurta
2025 J jnl
Hush! Protecting Secrets During Model Training: An Indistinguishability Approach.
CoRR
Arun Ganesh, Brendan McMahan, Milad Nasr, Thomas Steinke, Abhradeep Thakurta
2025 A* conf
It's My Data Too: Private ML for Datasets with Multi-User Training Examples.
ICML
Arun Ganesh, Ryan McKenna, Hugh Brendan McMahan, Adam Smith, Fan Wu
2025 J jnl
It's My Data Too: Private ML for Datasets with Multi-User Training Examples.
CoRR
Arun Ganesh, Ryan McKenna, Brendan McMahan, Adam Smith, Fan Wu
2025 — conf
Learning with User-Level Differential Privacy Under Fixed Compute Budgets.
SaTML
Zachary Charles, Arun Ganesh, Ryan McKenna, H. Brendan McMahan, Nicole Mitchell, Krishna Pillutla, Keith Rush
2025 A* conf
Near-Exact Privacy Amplification for Matrix Mechanisms.
ICLR
Christopher A. Choquette-Choo, Arun Ganesh, Saminul Haque, Thomas Steinke, Abhradeep Guha Thakurta
2025 B conf
Near-Optimal Rates for O(1)-Smooth DP-SCO with a Single Epoch and Large Batches.
ALT
Christopher A. Choquette-Choo, Arun Ganesh, Abhradeep Guha Thakurta
2025 J jnl
On Design Principles for Private Adaptive Optimizers.
CoRR
Arun Ganesh, Brendan McMahan, Abhradeep Thakurta
2025 J jnl
Recycling Scraps: Improving Private Learning by Leveraging Checkpoints]{Recycling Scraps: Improving Private Learning by Leveraging Checkpoints.
Proc. Priv. Enhancing Technol.
Virat Shejwalkar, Arun Ganesh, Rajiv Mathews, Yarong Mu, Shuang Song, Om Thakkar, Abhradeep Thakurta, Xinyi Zheng
2025 A* conf
The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD.
ICLR
Milad Nasr, Thomas Steinke, Borja Balle, Christopher A. Choquette-Choo, Arun Ganesh, Matthew Jagielski, Jamie Hayes, Abhradeep Guha Thakurta, Adam Smith, Andreas Terzis
2025 J jnl
Tighter Privacy Analysis for Truncated Poisson Sampling.
CoRR
Arun Ganesh
2024 A* conf
Correlated Noise Provably Beats Independent Noise for Differentially Private Learning.
ICLR
Christopher A. Choquette-Choo, Krishnamurthy Dj Dvijotham, Krishna Pillutla, Arun Ganesh, Thomas Steinke, Abhradeep Guha Thakurta
2024 J jnl
Fine-Tuning Large Language Models with User-Level Differential Privacy.
CoRR
Zachary Charles, Arun Ganesh, Ryan McKenna, H. Brendan McMahan, Nicole Mitchell, Krishna Pillutla, Keith Rush
2024 J jnl
Near Exact Privacy Amplification for Matrix Mechanisms.
CoRR
Christopher A. Choquette-Choo, Arun Ganesh, Saminul Haque, Thomas Steinke, Abhradeep Thakurta
2024 J jnl
Optimal Rates for DP-SCO with a Single Epoch and Large Batches.
CoRR
Christopher A. Choquette-Choo, Arun Ganesh, Abhradeep Thakurta
2024 A* conf
Privacy Amplification for Matrix Mechanisms.
ICLR
Christopher A. Choquette-Choo, Arun Ganesh, Thomas Steinke, Abhradeep Guha Thakurta
2024 J jnl
The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD.
CoRR
Thomas Steinke, Milad Nasr, Arun Ganesh, Borja Balle, Christopher A. Choquette-Choo, Matthew Jagielski, Jamie Hayes, Abhradeep Guha Thakurta, Adam Smith, Andreas Terzis
2024 J jnl
Tight Group-Level DP Guarantees for DP-SGD with Sampling via Mixture of Gaussians Mechanisms.
CoRR
Arun Ganesh
2023 A* conf
(Amplified) Banded Matrix Factorization: A unified approach to private training.
NeurIPS
Christopher A. Choquette-Choo, Arun Ganesh, Ryan McKenna, H. Brendan McMahan, John Rush, Abhradeep Guha Thakurta, Zheng Xu
2023 J jnl
(Amplified) Banded Matrix Factorization: A unified approach to private training.
CoRR
Christopher A. Choquette-Choo, Arun Ganesh, Ryan McKenna, H. Brendan McMahan, Keith Rush, Abhradeep Guha Thakurta, Zheng Xu
2023 J jnl
Correlated Noise Provably Beats Independent Noise for Differentially Private Learning.
CoRR
Christopher A. Choquette-Choo, Krishnamurthy Dvijotham, Krishna Pillutla, Arun Ganesh, Thomas Steinke, Abhradeep Thakurta
2023 A* conf
Faster Differentially Private Convex Optimization via Second-Order Methods.
NeurIPS
Arun Ganesh, Mahdi Haghifam, Thomas Steinke, Abhradeep Guha Thakurta
2023 J jnl
Faster Differentially Private Convex Optimization via Second-Order Methods.
CoRR
Arun Ganesh, Mahdi Haghifam, Thomas Steinke, Abhradeep Thakurta
2023 J jnl
Privacy Amplification for Matrix Mechanisms.
CoRR
Christopher A. Choquette-Choo, Arun Ganesh, Thomas Steinke, Abhradeep Thakurta
2023 A* conf
Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks.
NeurIPS
Daogao Liu, Arun Ganesh, Sewoong Oh, Abhradeep Guha Thakurta
2023 J jnl
Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks.
CoRR
Arun Ganesh, Daogao Liu, Sewoong Oh, Abhradeep Thakurta
2023 J jnl
Robust Algorithms for TSP and Steiner Tree.
ACM Trans. Algorithms
Arun Ganesh, Bruce M. Maggs, Debmalya Panigrahi
2023 J jnl
Universal Algorithms for Clustering Problems.
ACM Trans. Algorithms
Arun Ganesh, Bruce M. Maggs, Debmalya Panigrahi
2023 A* conf
Universality of Langevin Diffusion for Private Optimization, with Applications to Sampling from Rashomon Sets.
COLT
Arun Ganesh, Abhradeep Thakurta, Jalaj Upadhyay
2023 A* conf
Why Is Public Pretraining Necessary for Private Model Training?
ICML
Arun Ganesh, Mahdi Haghifam, Milad Nasr, Sewoong Oh, Thomas Steinke, Om Thakkar, Abhradeep Guha Thakurta, Lun Wang
2023 J jnl
Why Is Public Pretraining Necessary for Private Model Training?
CoRR
Arun Ganesh, Mahdi Haghifam, Milad Nasr, Sewoong Oh, Thomas Steinke, Om Thakkar, Abhradeep Thakurta, Lun Wang
2022 A* conf
How Compression and Approximation Affect Efficiency in String Distance Measures.
SODA
Arun Ganesh, Tomasz Kociumaka, Andrea Lincoln, Barna Saha
2022 — —
Improved Algorithms and Upper Bounds in Differential Privacy
Arun Ganesh
2022 J jnl
Langevin Diffusion: An Almost Universal Algorithm for Private Euclidean (Convex) Optimization.
CoRR
Arun Ganesh, Abhradeep Thakurta, Jalaj Upadhyay
2022 A* conf
Public Data-Assisted Mirror Descent for Private Model Training.
ICML
Ehsan Amid, Arun Ganesh, Rajiv Mathews, Swaroop Ramaswamy, Shuang Song, Thomas Steinke, Vinith M. Suriyakumar, Om Thakkar, Abhradeep Thakurta
2022 J jnl
Recycling Scraps: Improving Private Learning by Leveraging Intermediate Checkpoints.
CoRR
Virat Shejwalkar, Arun Ganesh, Rajiv Mathews, Om Thakkar, Abhradeep Thakurta
2021 J jnl
How Compression and Approximation Affect Efficiency in String Distance Measures.
CoRR
Arun Ganesh, Tomasz Kociumaka, Andrea Lincoln, Barna Saha
2021 J jnl
Online Service with Delay.
ACM Trans. Algorithms
Yossi Azar, Arun Ganesh, Rong Ge, Debmalya Panigrahi
2021 — conf
Privately Answering Counting Queries with Generalized Gaussian Mechanisms.
FORC
Arun Ganesh, Jiazheng Zhao
2021 J jnl
Public Data-Assisted Mirror Descent for Private Model Training.
CoRR
Ehsan Amid, Arun Ganesh, Rajiv Mathews, Swaroop Ramaswamy, Shuang Song, Thomas Steinke, Vinith M. Suriyakumar, Om Thakkar, Abhradeep Thakurta
2021 A* conf
Universal Algorithms for Clustering Problems.
ICALP
Arun Ganesh, Bruce M. Maggs, Debmalya Panigrahi
2021 J jnl
Universal Algorithms for Clustering.
CoRR
Arun Ganesh, Bruce M. Maggs, Debmalya Panigrahi
2020 A* conf
Faster Differentially Private Samplers via Rényi Divergence Analysis of Discretized Langevin MCMC.
NeurIPS
Arun Ganesh, Kunal Talwar
2020 J jnl
Faster Differentially Private Samplers via Rényi Divergence Analysis of Discretized Langevin MCMC.
CoRR
Arun Ganesh, Kunal Talwar
2020 C conf
Near-Linear Time Edit Distance for Indel Channels.
WABI
Arun Ganesh, Aaron Sy
2020 J jnl
Near-Linear Time Edit Distance for Indel Channels.
CoRR
Arun Ganesh, Aaron Sy
2020 J jnl
Privately Answering Counting Queries with Generalized Gaussian Mechanisms.
CoRR
Arun Ganesh, Jiazheng Zhao
2020 A* conf
Robust Algorithms for TSP and Steiner Tree.
ICALP
Arun Ganesh, Bruce M. Maggs, Debmalya Panigrahi
2020 J jnl
Robust Algorithms for TSP and Steiner Tree.
CoRR
Arun Ganesh, Bruce M. Maggs, Debmalya Panigrahi
2019 A* conf
Optimal sequence length requirements for phylogenetic tree reconstruction with indels.
STOC
Arun Ganesh, Qiuyi (Richard) Zhang
2018 J jnl
Optimal Sequence Length Requirements for Phylogenetic Tree Reconstruction with Indels.
CoRR
Arun Ganesh, Qiuyi (Richard) Zhang
2017 J jnl
Online Service with Delay.
CoRR
Yossi Azar, Arun Ganesh, Rong Ge, Debmalya Panigrahi
2017 A* conf
Online service with delay.
STOC
Yossi Azar, Arun Ganesh, Rong Ge, Debmalya Panigrahi