Or Sheffet
12 papers · 2014–2024 · 4 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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๐ Conference Polyglot ยท Bronze ๐บ๏ธ Taxonomy Completionist (25) ๐ฃ Hot Topic Early Bird ๐ Academic Marathon ยท Half ๐ Interdisciplinary Bridge ยท Silver
๐ฌ
Deep Specialist
(11)
๐
Keyword Champion
(2)
๐
Trend Setter
๐
Century Club ยท Bronze
๐๏ธ
Keyword Collector
(56)
Venues
Top co-authors
Research topics
Machine Learning
(12)
Application Areas
(11)
Mathematics & Optimization
(7)
Security & Privacy
(5)
Differential Privacy
(5)
Artificial Intelligence
(4)
Core Methods
(4)
Learning Types
(4)
Mathematics
(4)
Optimization
(4)
Optimization & Theory
(3)
Bayesian & Probabilistic ยท Machine Learning
(2)
Learning Paradigms
(2)
Bayesian & Probabilistic ยท Artificial Intelligence
(1)
Core AI
(1)
Keywords
differential privacy
(10)
sample complexity
(3)
ridge regression
(2)
stochastic optimization
(2)
confidence interval
(2)
johnson-lindenstrauss transform
(2)
linear regression
(2)
k-means clustering
(1)
tensor decomposition
(1)
convex optimization
(1)
mean estimation
(1)
maximum likelihood
(1)
hypothesis testing
(1)
statistical testing
(1)
mallows model
(1)
transfer learning
(1)
high-dimensional learning
(1)
distribution shift
(1)
exploration exploitation
(1)
parameter estimation
(1)
Papers
Differentially Private Equivalence Testing for Continuous Distributions and Applications
NeurIPS 2024
A Differentially Private Linear-Time fPTAS for the Minimum Enclosing Ball Problem
NeurIPS 2022
Transfer Learning In Differential Privacyโs Hybrid-Model
ICML 2022
Private k-Means Clustering with Stability Assumptions
AISTATS 2020
An Optimal Private Stochastic-MAB Algorithm based on Optimal Private Stopping Rule
ICML 2019
Differentially Private Algorithms for Learning Mixtures of Separated Gaussians
NeurIPS 2019
Locally Private Mean Estimation: Z-test and Tight Confidence Intervals
AISTATS 2019
Old Techniques in Differentially Private Linear Regression
ALT 2019
Differentially Private Contextual Linear Bandits
NeurIPS 2018
Locally Private Hypothesis Testing
ICML 2018
Differentially Private Ordinary Least Squares
ICML 2017
Learning Mixtures of Ranking Models
NeurIPS 2014