Hilal Asi
21 papers · 2019–2025 · 4 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (6) π§ Keyword Pioneer π Interdisciplinary Bridge π Conference Polyglot (4) π Cross-Pollinator (11)
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Cross-Pollinator
(11)
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Renaissance Researcher
(5)
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Taxonomy Completionist
(20)
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Deep Specialist
(13)
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Keyword Champion
(7)
ποΈ
Keyword Collector
(75)
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Century Club
(21)
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Prolific Year
(6)
π₯
Unstoppable
(7)
Conferences
ICML (9)
NIPS (8)
AISTATS (2)
COLT (2)
Top co-authors
Research topics
Keywords
differential privacy
(13)
stochastic convex optimization
(7)
mean estimation
(3)
stochastic optimization
(3)
gradient descent
(3)
regret bound
(3)
convex optimization
(2)
online learning
(2)
model-based method
(2)
expert prediction
(2)
online convex optimization
(2)
user-level privacy
(2)
proximal point method
(2)
principal component analysis
(2)
gradient estimation
(1)
privacy-preserving learning
(1)
distributed learning
(1)
excess risk
(1)
sample complexity
(1)
adversarial robustness
(1)
Papers
Faster Rates for Private Adversarial Bandits
ICML 2025
Tracking The Best Expert Privately
ICML 2025
Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages
ICML 2024
Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions
NIPS 2024
Faster Algorithms for User-Level Private Stochastic Convex Optimization
NIPS 2024
Universally Instance-Optimal Mechanisms for Private Statistical Estimation
COLT 2024
Private Online Learning via Lazy Algorithms
NIPS 2024
User-level Differentially Private Stochastic Convex Optimization: Efficient Algorithms with Optimal Rates
AISTATS 2024
Private Online Prediction from Experts: Separations and Faster Rates
COLT 2023
Fast Optimal Locally Private Mean Estimation via Random Projections
NIPS 2023
Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime
ICML 2023
From Robustness to Privacy and Back
ICML 2023
Optimal Algorithms for Mean Estimation under Local Differential Privacy
ICML 2022
Private optimization in the interpolation regime: faster rates and hardness results
ICML 2022
Stochastic Bias-Reduced Gradient Methods
NIPS 2021
Private Adaptive Gradient Methods for Convex Optimization
ICML 2021
Private Stochastic Convex Optimization: Optimal Rates in L1 Geometry
ICML 2021
Adapting to function difficulty and growth conditions in private optimization
NIPS 2021
Instance-optimality in differential privacy via approximate inverse sensitivity mechanisms
NIPS 2020
Minibatch Stochastic Approximate Proximal Point Methods
NIPS 2020
Modeling simple structures and geometry for better stochastic optimization algorithms
AISTATS 2019