Hilal Asi

Orcid: 0000-0003-3930-6958

According to our database1, Hilal Asi authored at least 22 papers between 2019 and 2024.

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Bibliography

2024
DP-Dueling: Learning from Preference Feedback without Compromising User Privacy.
CoRR, 2024

2023
User-level Differentially Private Stochastic Convex Optimization: Efficient Algorithms with Optimal Rates.
CoRR, 2023

Fast Optimal Locally Private Mean Estimation via Random Projections.
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.
Proceedings of the International Conference on Machine Learning, 2023

Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime.
Proceedings of the International Conference on Machine Learning, 2023

Private Online Prediction from Experts: Separations and Faster Rates.
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.
CoRR, 2022

Optimal Algorithms for Mean Estimation under Local Differential Privacy.
Proceedings of the International Conference on Machine Learning, 2022

Private optimization in the interpolation regime: faster rates and hardness results.
Proceedings of the International Conference on Machine Learning, 2022

2021
Private Stochastic Convex Optimization: Optimal Rates in 𝓁<sub>1</sub> Geometry.
CoRR, 2021

Adapting to function difficulty and growth conditions in private optimization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Stochastic Bias-Reduced Gradient Methods.
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.
Proceedings of the 38th International Conference on Machine Learning, 2021

Private Adaptive Gradient Methods for Convex Optimization.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Near Instance-Optimality in Differential Privacy.
CoRR, 2020

Finding Planted Cliques in Sublinear Time.
CoRR, 2020

Instance-optimality in differential privacy via approximate inverse sensitivity mechanisms.
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.
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.
IEEE Trans. Inf. Theory, 2019

Stochastic (Approximate) Proximal Point Methods: Convergence, Optimality, and Adaptivity.
SIAM J. Optim., 2019

Element Level Differential Privacy: The Right Granularity of Privacy.
CoRR, 2019

Modeling simple structures and geometry for better stochastic optimization algorithms.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019


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