Arun Ganesh

CoRR, 2024

2023

Universal Algorithms for Clustering Problems.

[BibT_eX]

[DOI]

Bruce M. Maggs

Debmalya Panigrahi

ACM Trans. Algorithms, April, 2023

Robust Algorithms for TSP and Steiner Tree.

[BibT_eX]

[DOI]

Bruce M. Maggs

Debmalya Panigrahi

ACM Trans. Algorithms, April, 2023

Privacy Amplification for Matrix Mechanisms.

[BibT_eX]

[DOI]

Thomas Steinke

CoRR, 2023

Correlated Noise Provably Beats Independent Noise for Differentially Private Learning.

[BibT_eX]

[DOI]

Krishnamurthy Dvijotham

CoRR, 2023

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

[BibT_eX]

[DOI]

Zheng Xu

CoRR, 2023

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

[BibT_eX]

[DOI]

Daogao Liu

Sewoong Oh

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.

[BibT_eX]

[DOI]

Mahdi Haghifam

Thomas Steinke

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.

[BibT_eX]

[DOI]

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?

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Jalaj Upadhyay

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

2022

Improved Algorithms and Upper Bounds in Differential Privacy

[BibT_eX]

[DOI]

PhD thesis, 2022

Recycling Scraps: Improving Private Learning by Leveraging Intermediate Checkpoints.

[BibT_eX]

[DOI]

CoRR, 2022

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

[BibT_eX]

[DOI]

Jalaj Upadhyay

CoRR, 2022

How Compression and Approximation Affect Efficiency in String Distance Measures.

[BibT_eX]

[DOI]

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

Public Data-Assisted Mirror Descent for Private Model Training.

[BibT_eX]

[DOI]

Vinith M. Suriyakumar

Om Thakkar

Proceedings of the International Conference on Machine Learning, 2022

2021

Online Service with Delay.

[BibT_eX]

[DOI]

ACM Trans. Algorithms, 2021

Universal Algorithms for Clustering.

[BibT_eX]

[DOI]

Bruce M. Maggs

Debmalya Panigrahi

CoRR, 2021

Privately Answering Counting Queries with Generalized Gaussian Mechanisms.

[BibT_eX]

[DOI]

Jiazheng Zhao

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

2020

Near-Linear Time Edit Distance for Indel Channels.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]