Asi, Hilal

22 publications

ICML 2025 Faster Rates for Private Adversarial Bandits Hilal Asi, Vinod Raman, Kunal Talwar

NeurIPS 2025 PREAMBLE: Private and Efficient Aggregation via Block Sparse Vectors Hilal Asi, Vitaly Feldman, Hannah Keller, Guy N. Rothblum, Kunal Talwar

ICML 2025 Tracking the Best Expert Privately Hilal Asi, Vinod Raman, Aadirupa Saha

NeurIPS 2024 Faster Algorithms for User-Level Private Stochastic Convex Optimization Andrew Lowy, Daogao Liu, Hilal Asi

NeurIPS 2024 Private Online Learning via Lazy Algorithms Hilal Asi, Tomer Koren, Daogao Liu, Kunal Talwar

NeurIPS 2024 Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions Hilal Asi, Daogao Liu, Kevin Tian

ICML 2024 Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy Nguyen, Kunal Talwar, Samson Zhou

COLT 2024 Universally Instance-Optimal Mechanisms for Private Statistical Estimation Hilal Asi, John C. Duchi, Saminul Haque, Zewei Li, Feng Ruan

AISTATS 2024 User-Level Differentially Private Stochastic Convex Optimization: Efficient Algorithms with Optimal Rates Daogao Liu, Hilal Asi

NeurIPS 2023 Fast Optimal Locally Private Mean Estimation via Random Projections Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy Nguyen, Kunal Talwar

ICML 2023 From Robustness to Privacy and Back Hilal Asi, Jonathan Ullman, Lydia Zakynthinou

ICML 2023 Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar

COLT 2023 Private Online Prediction from Experts: Separations and Faster Rates Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar

ICML 2022 Optimal Algorithms for Mean Estimation Under Local Differential Privacy Hilal Asi, Vitaly Feldman, Kunal Talwar

ICML 2022 Private Optimization in the Interpolation Regime: Faster Rates and Hardness Results Hilal Asi, Karan Chadha, Gary Cheng, John Duchi

NeurIPS 2021 Adapting to Function Difficulty and Growth Conditions in Private Optimization Hilal Asi, Daniel Levy, John C. Duchi

ICML 2021 Private Adaptive Gradient Methods for Convex Optimization Hilal Asi, John Duchi, Alireza Fallah, Omid Javidbakht, Kunal Talwar

ICML 2021 Private Stochastic Convex Optimization: Optimal Rates in L1 Geometry Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar

NeurIPS 2021 Stochastic Bias-Reduced Gradient Methods Hilal Asi, Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford

NeurIPS 2020 Instance-Optimality in Differential Privacy via Approximate Inverse Sensitivity Mechanisms Hilal Asi, John C. Duchi

NeurIPS 2020 Minibatch Stochastic Approximate Proximal Point Methods Hilal Asi, Karan Chadha, Gary Cheng, John C. Duchi

AISTATS 2019 Modeling Simple Structures and Geometry for Better Stochastic Optimization Algorithms Hilal Asi, John C. Duchi