Hilal Asi

According to our database, Hilal Asi authored at least 28 papers between 2019 and 2024.

Collaborative distances:

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

2024

Faster Algorithms for User-Level Private Stochastic Convex Optimization.

Andrew Lowy, Daogao Liu, Hilal Asi

CoRR, 2024

Scalable Private Search with Wally.

Hilal Asi, Fabian Boemer, Nicholas Genise, Muhammad Haris Mughees, Tabitha Ogilvie, Rehan Rishi, Guy N. Rothblum, Kunal Talwar, Karl Tarbe, Ruiyu Zhu, Marco Zuliani

CoRR, 2024

Private Online Learning via Lazy Algorithms.

Hilal Asi, Tomer Koren, Daogao Liu, Kunal Talwar

CoRR, 2024

Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions.

Hilal Asi, Daogao Liu, Kevin Tian

CoRR, 2024

DP-Dueling: Learning from Preference Feedback without Compromising User Privacy.

Aadirupa Saha, Hilal Asi

CoRR, 2024

Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages.

Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar, Samson Zhou

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Universally Instance-Optimal Mechanisms for Private Statistical Estimation.

Hilal Asi, John C. Duchi, Saminul Haque, Zewei Li, Feng Ruan

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

User-level Differentially Private Stochastic Convex Optimization: Efficient Algorithms with Optimal Rates.

Daogao Liu, Hilal Asi

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Fast Optimal Locally Private Mean Estimation via Random Projections.

Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar

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

From Robustness to Privacy and Back.

Hilal Asi, Jonathan R. Ullman, Lydia Zakynthinou

Proceedings of the International Conference on Machine Learning, 2023

Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime.

Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar

Proceedings of the International Conference on Machine Learning, 2023

Private Online Prediction from Experts: Separations and Faster Rates.

Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar

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

2022

How many labelers do you have? A closer look at gold-standard labels.

Chen Cheng, Hilal Asi, John C. Duchi

CoRR, 2022

Optimal Algorithms for Mean Estimation under Local Differential Privacy.

Hilal Asi, Vitaly Feldman, Kunal Talwar

Proceedings of the International Conference on Machine Learning, 2022

Private optimization in the interpolation regime: faster rates and hardness results.

Hilal Asi, Karan N. Chadha, Gary Cheng, John C. Duchi

Proceedings of the International Conference on Machine Learning, 2022

2021

Private Stochastic Convex Optimization: Optimal Rates in 𝓁₁ Geometry.

Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar

CoRR, 2021

Adapting to function difficulty and growth conditions in private optimization.

Hilal Asi, Daniel Levy, John C. Duchi

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Stochastic Bias-Reduced Gradient Methods.

Hilal Asi, Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Private Stochastic Convex Optimization: Optimal Rates in L1 Geometry.

Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar

Proceedings of the 38th International Conference on Machine Learning, 2021

Private Adaptive Gradient Methods for Convex Optimization.

Hilal Asi, John C. Duchi, Alireza Fallah, Omid Javidbakht, Kunal Talwar

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Near Instance-Optimality in Differential Privacy.

Hilal Asi, John C. Duchi

CoRR, 2020

Finding Planted Cliques in Sublinear Time.

Jay Mardia, Hilal Asi, Kabir Aladin Chandrasekher

CoRR, 2020

Instance-optimality in differential privacy via approximate inverse sensitivity mechanisms.

Hilal Asi, John C. Duchi

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

Minibatch Stochastic Approximate Proximal Point Methods.

Hilal Asi, Karan N. Chadha, Gary Cheng, John C. Duchi

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

2019

Nearly Optimal Constructions of PIR and Batch Codes.

Hilal Asi, Eitan Yaakobi

IEEE Trans. Inf. Theory, 2019

Stochastic (Approximate) Proximal Point Methods: Convergence, Optimality, and Adaptivity.

Hilal Asi, John C. Duchi

SIAM J. Optim., 2019

Element Level Differential Privacy: The Right Granularity of Privacy.

Hilal Asi, John C. Duchi, Omid Javidbakht

CoRR, 2019

Modeling simple structures and geometry for better stochastic optimization algorithms.

Hilal Asi, John C. Duchi

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019