Raef Bassily
28 papers · 2017–2025 · 6 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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🗺️ Taxonomy Completionist (33) 🏃 Academic Marathon · Sprint 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird
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Deep Specialist
(23)
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Keyword Champion
(3)
🧭
Keyword Pioneer
💎
Century Club · Bronze
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Unstoppable · Bronze
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Prolific Year · Productive
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Keyword Collector
(100)
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Trend Setter
Top co-authors
Research topics
Machine Learning
(28)
Application Areas
(24)
Optimization & Theory · Machine Learning
(21)
Mathematics & Optimization
(9)
Security & Privacy
(9)
Differential Privacy
(8)
Optimization
(8)
Core Methods
(7)
Learning Types
(4)
Artificial Intelligence
(3)
Deep Learning
(3)
Core AI
(2)
Learning Paradigms
(2)
Mathematics
(2)
Optimization & Theory · Deep Learning
(2)
Keywords
differential privacy
(26)
stochastic gradient descent
(5)
public data
(4)
stochastic optimization
(4)
stochastic convex optimization
(4)
sample complexity
(4)
private learning
(4)
generalization guarantee
(3)
generalized linear model
(3)
vc dimension
(3)
local privacy
(3)
model selection
(2)
heavy hitter
(2)
pac learning
(2)
convex optimization
(2)
domain adaptation
(2)
convergence rate
(2)
generalization error
(2)
non-convex optimization
(2)
privacy-preserving machine learning
(2)
Papers
Private Model Personalization Revisited
ICML 2025
Differentially Private Domain Adaptation with Theoretical Guarantees
ICML 2024
Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates
ALT 2024
Differentially Private Worst-group Risk Minimization
ICML 2024
Private Algorithms for Stochastic Saddle Points and Variational Inequalities: Beyond Euclidean Geometry
NeurIPS 2024
Public-data Assisted Private Stochastic Optimization: Power and Limitations
NeurIPS 2024
Differentially Private Algorithms for the Stochastic Saddle Point Problem with Optimal Rates for the Strong Gap
COLT 2023
Faster Rates of Convergence to Stationary Points in Differentially Private Optimization
ICML 2023
Principled Approaches for Private Adaptation from a Public Source
AISTATS 2023
User-level Private Stochastic Convex Optimization with Optimal Rates
ICML 2023
Differentially Private Generalized Linear Models Revisited
NeurIPS 2022
Differentially Private Learning with Margin Guarantees
NeurIPS 2022
Open Problem: Better Differentially Private Learning Algorithms with Margin Guarantees
COLT 2022
Task-level Differentially Private Meta Learning
NeurIPS 2022
Differentially Private Stochastic Optimization: New Results in Convex and Non-Convex Settings
NeurIPS 2021
Non-Euclidean Differentially Private Stochastic Convex Optimization
COLT 2021
Learning from Mixtures of Private and Public Populations
NeurIPS 2020
Practical Locally Private Heavy Hitters
JMLR 2020
Privately Answering Classification Queries in the Agnostic PAC Model
ALT 2020
Private Query Release Assisted by Public Data
ICML 2020
Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses
NeurIPS 2020
Limits of Private Learning with Access to Public Data
NeurIPS 2019
Linear Queries Estimation with Local Differential Privacy
AISTATS 2019
Private Stochastic Convex Optimization with Optimal Rates
NeurIPS 2019
Learners that Use Little Information
ALT 2018
Model-Agnostic Private Learning
NeurIPS 2018
The Power of Interpolation: Understanding the Effectiveness of SGD in Modern Over-parametrized Learning
ICML 2018
Practical Locally Private Heavy Hitters
NeurIPS 2017