Hilal Asi

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 39

Top Topics

Semidefinite Program

Differential Privacy

Statistical Estimation

Top Venues

Publications

Hilal Asi, Tomer Koren, Daogao Liu, Kunal Talwar
Private Online Learning via Lazy Algorithms. CoRR (2024)
Hilal Asi, Fabian Boemer, Nicholas Genise, Muhammad Haris Mughees, Tabitha Ogilvie, Rehan Rishi, Guy N. Rothblum, Kunal Talwar, Karl Tarbe, Ruiyu Zhu, Marco Zuliani
Scalable Private Search with Wally. CoRR (2024)
Daogao Liu, Hilal Asi
User-level Differentially Private Stochastic Convex Optimization: Efficient Algorithms with Optimal Rates. AISTATS (2024)
Aadirupa Saha, Hilal Asi
DP-Dueling: Learning from Preference Feedback without Compromising User Privacy. CoRR (2024)
Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar, Samson Zhou
Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages. CoRR (2024)
Hilal Asi, Daogao Liu, Kevin Tian
Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions. CoRR (2024)
Hilal Asi, John C. Duchi, Saminul Haque, Zewei Li, Feng Ruan
Universally Instance-Optimal Mechanisms for Private Statistical Estimation. COLT (2024)
Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar
Private Online Prediction from Experts: Separations and Faster Rates. COLT (2023)
Hilal Asi, Jonathan R. Ullman, Lydia Zakynthinou
From Robustness to Privacy and Back. ICML (2023)
Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar
Fast Optimal Locally Private Mean Estimation via Random Projections. NeurIPS (2023)
Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar
Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime. ICML (2023)
Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar
Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime. CoRR (2023)
Hilal Asi, Jonathan R. Ullman, Lydia Zakynthinou
From Robustness to Privacy and Back. CoRR (2023)
Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar
Fast Optimal Locally Private Mean Estimation via Random Projections. CoRR (2023)
Hilal Asi, Daogao Liu
User-level Differentially Private Stochastic Convex Optimization: Efficient Algorithms with Optimal Rates. CoRR (2023)
Hilal Asi, Vitaly Feldman, Kunal Talwar
Optimal Algorithms for Mean Estimation under Local Differential Privacy. CoRR (2022)
Hilal Asi, Karan N. Chadha, Gary Cheng, John Duchi
Private optimization in the interpolation regime: faster rates and hardness results. ICML (2022)
Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar
Private Online Prediction from Experts: Separations and Faster Rates. CoRR (2022)
Hilal Asi, Karan N. Chadha, Gary Cheng, John Duchi
Private optimization in the interpolation regime: faster rates and hardness results. CoRR (2022)
Hilal Asi, Vitaly Feldman, Kunal Talwar
Optimal Algorithms for Mean Estimation under Local Differential Privacy. ICML (2022)
Chen Cheng, Hilal Asi, John Duchi
How many labelers do you have? A closer look at gold-standard labels. CoRR (2022)
Hilal Asi, Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford
Stochastic Bias-Reduced Gradient Methods. CoRR (2021)
Hilal Asi, John C. Duchi, Alireza Fallah, Omid Javidbakht, Kunal Talwar
Private Adaptive Gradient Methods for Convex Optimization. ICML (2021)
Hilal Asi, Daniel Levy, John C. Duchi
Adapting to function difficulty and growth conditions in private optimization. NeurIPS (2021)
Hilal Asi, John C. Duchi, Alireza Fallah, Omid Javidbakht, Kunal Talwar
Private Adaptive Gradient Methods for Convex Optimization. CoRR (2021)
Hilal Asi, Daniel Levy, John C. Duchi
Adapting to Function Difficulty and Growth Conditions in Private Optimization. CoRR (2021)
Hilal Asi, Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford
Stochastic Bias-Reduced Gradient Methods. NeurIPS (2021)
Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar
Geometry. CoRR (2021)
Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar
Private Stochastic Convex Optimization: Optimal Rates in L1 Geometry. ICML (2021)
Hilal Asi, John C. Duchi
Near Instance-Optimality in Differential Privacy. CoRR (2020)
Jay Mardia, Hilal Asi, Kabir Aladin Chandrasekher
Finding Planted Cliques in Sublinear Time. CoRR (2020)
Hilal Asi, Karan N. Chadha, Gary Cheng, John C. Duchi
Minibatch Stochastic Approximate Proximal Point Methods. NeurIPS (2020)
Hilal Asi, John C. Duchi
Instance-optimality in differential privacy via approximate inverse sensitivity mechanisms. NeurIPS (2020)
Hilal Asi, John C. Duchi
Stochastic (Approximate) Proximal Point Methods: Convergence, Optimality, and Adaptivity. SIAM J. Optim. 29 (3) (2019)
Hilal Asi, John C. Duchi
Modeling simple structures and geometry for better stochastic optimization algorithms. AISTATS (2019)
Hilal Asi, Eitan Yaakobi
Nearly Optimal Constructions of PIR and Batch Codes. IEEE Trans. Inf. Theory 65 (2) (2019)
Hilal Asi, John C. Duchi, Omid Javidbakht
Element Level Differential Privacy: The Right Granularity of Privacy. CoRR (2019)
Hilal Asi, Eitan Yaakobi
Nearly Optimal Constructions of PIR and Batch Codes. CoRR (2017)
Hilal Asi, Eitan Yaakobi
Nearly optimal constructions of PIR and batch codes. ISIT (2017)