Mark Bun
16 papers · 2017–2026 · 5 conferences · across top CS/AI conferences
Achievements
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🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (5) 🏃 Academic Marathon (7) 🐝 Cross-Pollinator (15)
🧭
Keyword Pioneer
🌍
Conference Polyglot
(5)
🔬
Deep Specialist
(12)
💎
Century Club
(15)
📈
Trend Setter
🔥
Unstoppable
(6)
Conferences
NIPS (7)
ALT (3)
ICML (3)
COLT (2)
JMLR (1)
Top co-authors
Research topics
Keywords
differential privacy
(12)
private learning
(6)
pac learning
(6)
sample complexity
(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)
multiclass classification
(1)
hypothesis testing
(1)
computational efficiency
(1)
density estimation
(1)
multiclass learning
(1)
privacy-preserving learning
(1)
data summarization
(1)
large-margin halfspaces
(1)
Papers
Privately Learning Decision Lists and a Differentially Private Winnow
ALT 2026
Not All Learnable Distribution Classes are Privately Learnable
ALT 2024
Oracle-Efficient Differentially Private Learning with Public Data
NIPS 2024
Optimal Hypothesis Selection in (Almost) Linear Time
NIPS 2024
Private PAC Learning May be Harder than Online Learning
ALT 2024
Hypothesis Selection with Memory Constraints
NIPS 2023
Strong Memory Lower Bounds for Learning Natural Models
COLT 2022
Differentially Private Correlation Clustering
ICML 2021
Multiclass versus Binary Differentially Private PAC Learning
NIPS 2021
New Oracle-Efficient Algorithms for Private Synthetic Data Release
ICML 2020
A Computational Separation between Private Learning and Online Learning
NIPS 2020
Efficient, Noise-Tolerant, and Private Learning via Boosting
COLT 2020
Private Hypothesis Selection
NIPS 2019
Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation
NIPS 2019
Simultaneous Private Learning of Multiple Concepts
JMLR 2019
Differentially Private Submodular Maximization: Data Summarization in Disguise
ICML 2017