Raef Bassily
28 papers · 2017–2025 · 6 conferences · across top CS/AI conferences
Achievements
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π Interdisciplinary Bridge π Conference Polyglot (6) π§ Keyword Pioneer π£ Hot Topic Early Bird π Academic Marathon (8)
πΊοΈ
Taxonomy Completionist
(34)
π£
Hot Topic Early Bird
π
Interdisciplinary Bridge
π¬
Deep Specialist
(23)
π
Keyword Champion
(2)
π±
Topic Pioneer
ποΈ
Keyword Collector
(82)
π
Century Club
(28)
π₯
Unstoppable
(9)
π
Trend Setter
β‘
Prolific Year
(5)
Conferences
NIPS (12)
ICML (7)
ALT (3)
COLT (3)
AISTATS (2)
JMLR (1)
Top co-authors
Research topics
Keywords
differential privacy
(23)
sample complexity
(4)
stochastic gradient descent
(4)
public datum
(4)
stochastic convex optimization
(4)
stochastic optimization
(4)
private learning
(4)
generalization guarantee
(3)
generalized linear model
(3)
vc dimension
(3)
local privacy
(3)
pac learning
(2)
neural network
(2)
model selection
(2)
excess population risk
(2)
margin guarantee
(2)
heavy hitter
(2)
non-convex optimization
(2)
convergence rate
(2)
mean estimation
(1)
Papers
Private Model Personalization Revisited
ICML 2025
Public-data Assisted Private Stochastic Optimization: Power and Limitations
NIPS 2024
Differentially Private Worst-group Risk Minimization
ICML 2024
Differentially Private Domain Adaptation with Theoretical Guarantees
ICML 2024
Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates
ALT 2024
Private Algorithms for Stochastic Saddle Points and Variational Inequalities: Beyond Euclidean Geometry
NIPS 2024
User-level Private Stochastic Convex Optimization with Optimal Rates
ICML 2023
Principled Approaches for Private Adaptation from a Public Source
AISTATS 2023
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
Open Problem: Better Differentially Private Learning Algorithms with Margin Guarantees
COLT 2022
Differentially Private Learning with Margin Guarantees
NIPS 2022
Differentially Private Generalized Linear Models Revisited
NIPS 2022
Task-level Differentially Private Meta Learning
NIPS 2022
Non-Euclidean Differentially Private Stochastic Convex Optimization
COLT 2021
Differentially Private Stochastic Optimization: New Results in Convex and Non-Convex Settings
NIPS 2021
Learning from Mixtures of Private and Public Populations
NIPS 2020
Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses
NIPS 2020
Practical Locally Private Heavy Hitters
JMLR 2020
Private Query Release Assisted by Public Data
ICML 2020
Privately Answering Classification Queries in the Agnostic PAC Model
ALT 2020
Linear Queries Estimation with Local Differential Privacy
AISTATS 2019
Limits of Private Learning with Access to Public Data
NIPS 2019
Private Stochastic Convex Optimization with Optimal Rates
NIPS 2019
Learners that Use Little Information
ALT 2018
Model-Agnostic Private Learning
NIPS 2018
The Power of Interpolation: Understanding the Effectiveness of SGD in Modern Over-parametrized Learning
ICML 2018
Practical Locally Private Heavy Hitters
NIPS 2017