Arun Ganesh

According to our database, Arun Ganesh authored at least 26 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Near Exact Privacy Amplification for Matrix Mechanisms.

Christopher A. Choquette-Choo, Arun Ganesh, Saminul Haque, Thomas Steinke, Abhradeep Thakurta

CoRR, 2024

The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD.

Thomas Steinke, Milad Nasr, Arun Ganesh, Borja Balle, Christopher A. Choquette-Choo, Matthew Jagielski, Jamie Hayes, Abhradeep Guha Thakurta, Adam D. Smith, Andreas Terzis

CoRR, 2024

Fine-Tuning Large Language Models with User-Level Differential Privacy.

Zachary Charles, Arun Ganesh, Ryan McKenna, H. Brendan McMahan, Nicole Mitchell, Krishna Pillutla, Keith Rush

CoRR, 2024

Optimal Rates for DP-SCO with a Single Epoch and Large Batches.

Christopher A. Choquette-Choo, Arun Ganesh, Abhradeep Thakurta

CoRR, 2024

Tight Group-Level DP Guarantees for DP-SGD with Sampling via Mixture of Gaussians Mechanisms.

Arun Ganesh

CoRR, 2024

Privacy Amplification for Matrix Mechanisms.

Christopher A. Choquette-Choo, Arun Ganesh, Thomas Steinke, Abhradeep Guha Thakurta

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Correlated Noise Provably Beats Independent Noise for Differentially Private Learning.

Christopher A. Choquette-Choo, Krishnamurthy Dj Dvijotham, Krishna Pillutla, Arun Ganesh, Thomas Steinke, Abhradeep Guha Thakurta

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Universal Algorithms for Clustering Problems.

Arun Ganesh, Bruce M. Maggs, Debmalya Panigrahi

ACM Trans. Algorithms, April, 2023

Robust Algorithms for TSP and Steiner Tree.

Arun Ganesh, Bruce M. Maggs, Debmalya Panigrahi

ACM Trans. Algorithms, April, 2023

(Amplified) Banded Matrix Factorization: A unified approach to private training.

Christopher A. Choquette-Choo, Arun Ganesh, Ryan McKenna, H. Brendan McMahan, Keith Rush, Abhradeep Guha Thakurta, Zheng Xu

CoRR, 2023

Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks.

Daogao Liu, Arun Ganesh, Sewoong Oh, Abhradeep Guha Thakurta

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Faster Differentially Private Convex Optimization via Second-Order Methods.

Arun Ganesh, Mahdi Haghifam, Thomas Steinke, Abhradeep Guha Thakurta

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

(Amplified) Banded Matrix Factorization: A unified approach to private training.

Christopher A. Choquette-Choo, Arun Ganesh, Ryan McKenna, H. Brendan McMahan, John Rush, Abhradeep Guha Thakurta, Zheng Xu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Why Is Public Pretraining Necessary for Private Model Training?

Arun Ganesh, Mahdi Haghifam, Milad Nasr, Sewoong Oh, Thomas Steinke, Om Thakkar, Abhradeep Guha Thakurta, Lun Wang

Proceedings of the International Conference on Machine Learning, 2023

Universality of Langevin Diffusion for Private Optimization, with Applications to Sampling from Rashomon Sets.

Arun Ganesh, Abhradeep Thakurta, Jalaj Upadhyay

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022

Improved Algorithms and Upper Bounds in Differential Privacy

Arun Ganesh

PhD thesis, 2022

Recycling Scraps: Improving Private Learning by Leveraging Intermediate Checkpoints.

Virat Shejwalkar, Arun Ganesh, Rajiv Mathews, Om Thakkar, Abhradeep Thakurta

CoRR, 2022

Langevin Diffusion: An Almost Universal Algorithm for Private Euclidean (Convex) Optimization.

Arun Ganesh, Abhradeep Thakurta, Jalaj Upadhyay

CoRR, 2022

How Compression and Approximation Affect Efficiency in String Distance Measures.

Arun Ganesh, Tomasz Kociumaka, Andrea Lincoln, Barna Saha

Proceedings of the 2022 ACM-SIAM Symposium on Discrete Algorithms, 2022

Public Data-Assisted Mirror Descent for Private Model Training.

Ehsan Amid, Arun Ganesh, Rajiv Mathews, Swaroop Ramaswamy, Shuang Song, Thomas Steinke, Vinith M. Suriyakumar, Om Thakkar, Abhradeep Thakurta

Proceedings of the International Conference on Machine Learning, 2022

2021

Online Service with Delay.

Yossi Azar, Arun Ganesh, Rong Ge, Debmalya Panigrahi

ACM Trans. Algorithms, 2021

Universal Algorithms for Clustering.

Arun Ganesh, Bruce M. Maggs, Debmalya Panigrahi

CoRR, 2021

Privately Answering Counting Queries with Generalized Gaussian Mechanisms.

Arun Ganesh, Jiazheng Zhao

Proceedings of the 2nd Symposium on Foundations of Responsible Computing, 2021

2020

Near-Linear Time Edit Distance for Indel Channels.

Arun Ganesh, Aaron Sy

Proceedings of the 20th International Workshop on Algorithms in Bioinformatics, 2020

Faster Differentially Private Samplers via Rényi Divergence Analysis of Discretized Langevin MCMC.

Arun Ganesh, Kunal Talwar

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Optimal sequence length requirements for phylogenetic tree reconstruction with indels.

Arun Ganesh, Qiuyi (Richard) Zhang

Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 2019