Modeling simple structures and geometry for better stochastic optimization algorithms. - Hilal Asi; John C. Duchi (AISTATS, 2019)

Element Level Differential Privacy: The Right Granularity of Privacy. - Hilal Asi; John C. Duchi; Omid Javidbakht (CoRR, 2019)

Stochastic (Approximate) Proximal Point Methods: Convergence, Optimality, and Adaptivity. - Hilal Asi; John C. Duchi (SIAM J. Optim., 2019)

Nearly Optimal Constructions of PIR and Batch Codes. - Hilal Asi; Eitan Yaakobi (IEEE Trans. Inf. Theory, 2019)

Minibatch Stochastic Approximate Proximal Point Methods. - Hilal Asi; Karan N. Chadha; Gary Cheng 004; John C. Duchi (NeurIPS, 2020)

Instance-optimality in differential privacy via approximate inverse sensitivity mechanisms. - Hilal Asi; John C. Duchi (NeurIPS, 2020)

Finding Planted Cliques in Sublinear Time. - Jay Mardia; Hilal Asi; Kabir Aladin Chandrasekher (CoRR, 2020)

Near Instance-Optimality in Differential Privacy. - Hilal Asi; John C. Duchi (CoRR, 2020)

Private Adaptive Gradient Methods for Convex Optimization. - Hilal Asi; John C. Duchi; Alireza Fallah 001; Omid Javidbakht; Kunal Talwar (ICML, 2021)

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

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

Adapting to function difficulty and growth conditions in private optimization. - Hilal Asi; Daniel Levy; John C. Duchi (NeurIPS, 2021)

Private Stochastic Convex Optimization: Optimal Rates in 𝓁1 Geometry. - Hilal Asi; Vitaly Feldman; Tomer Koren; Kunal Talwar (CoRR, 2021)

Private optimization in the interpolation regime: faster rates and hardness results. - Hilal Asi; Karan N. Chadha; Gary Cheng 004; John C. Duchi (ICML, 2022)

Optimal Algorithms for Mean Estimation under Local Differential Privacy. - Hilal Asi; Vitaly Feldman; Kunal Talwar (ICML, 2022)

How many labelers do you have? A closer look at gold-standard labels. - Chen Cheng; Hilal Asi; John C. Duchi (CoRR, 2022)

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

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

From Robustness to Privacy and Back. - Hilal Asi; Jonathan R. Ullman; Lydia Zakynthinou (ICML, 2023)

Fast Optimal Locally Private Mean Estimation via Random Projections. - Hilal Asi; Vitaly Feldman; Jelani Nelson; Huy L. Nguyen; Kunal Talwar (NeurIPS, 2023)

User-level Differentially Private Stochastic Convex Optimization: Efficient Algorithms with Optimal Rates. - Daogao Liu; Hilal Asi (AISTATS, 2024)

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

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

DP-Dueling: Learning from Preference Feedback without Compromising User Privacy. - Aadirupa Saha; 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)

PREAMBLE: Private and Efficient Aggregation of Block Sparse Vectors and Applications. - Hilal Asi; Vitaly Feldman; Hannah Keller; Guy N. Rothblum; Kunal Talwar (IACR Cryptol. ePrint Arch., 2025)

Tracking the Best Expert Privately. - Aadirupa Saha; Vinod Raman; Hilal Asi (CoRR, 2025)

On Privately Estimating a Single Parameter. - Hilal Asi; John C. Duchi; Kunal Talwar (CoRR, 2025)

ABoN: Adaptive Best-of-N Alignment. - Vinod Raman; Hilal Asi; Satyen Kale (CoRR, 2025)

Faster Rates for Private Adversarial Bandits. - Hilal Asi; Vinod Raman; Kunal Talwar (CoRR, 2025)