Mark Bun
16 papers · 2017–2026 · 5 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (20) π Academic Marathon Β· Sprint π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
π
Keyword Champion
(6)
π¬
Deep Specialist
(12)
ποΈ
Keyword Collector
(55)
π
Trend Setter
π
Century Club Β· Bronze
π₯
Unstoppable Β· Bronze
Venues
Top co-authors
Research topics
Machine Learning
(16)
Optimization & Theory
(13)
Application Areas
(12)
Security & Privacy
(6)
Differential Privacy
(6)
Mathematics & Optimization
(4)
Learning Types
(4)
Core Methods
(2)
Mathematics
(2)
Optimization
(2)
Artificial Intelligence
(1)
Computer Science
(1)
Foundations
(1)
Learning Paradigms
(1)
Keywords
differential privacy
(12)
sample complexity
(8)
private learning
(6)
pac learning
(6)
learning theory
(3)
online learning
(3)
total variation distance
(2)
hypothesis selection
(2)
distribution learning
(2)
computational complexity
(2)
optimization oracle
(2)
statistical query
(1)
large margin classification
(1)
hypothesis testing
(1)
computational efficiency
(1)
density estimation
(1)
data summarization
(1)
privacy-preserving learning
(1)
large-margin halfspaces
(1)
correlation clustering
(1)
Papers
Privately Learning Decision Lists and a Differentially Private Winnow
ALT 2026
Not All Learnable Distribution Classes are Privately Learnable
ALT 2024
Optimal Hypothesis Selection in (Almost) Linear Time
NeurIPS 2024
Oracle-Efficient Differentially Private Learning with Public Data
NeurIPS 2024
Private PAC Learning May be Harder than Online Learning
ALT 2024
Hypothesis Selection with Memory Constraints
NeurIPS 2023
Strong Memory Lower Bounds for Learning Natural Models
COLT 2022
Differentially Private Correlation Clustering
ICML 2021
Multiclass versus Binary Differentially Private PAC Learning
NeurIPS 2021
A Computational Separation between Private Learning and Online Learning
NeurIPS 2020
Efficient, Noise-Tolerant, and Private Learning via Boosting
COLT 2020
New Oracle-Efficient Algorithms for Private Synthetic Data Release
ICML 2020
Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation
NeurIPS 2019
Private Hypothesis Selection
NeurIPS 2019
Simultaneous Private Learning of Multiple Concepts
JMLR 2019
Differentially Private Submodular Maximization: Data Summarization in Disguise
ICML 2017