Shai Ben-David
29 papers · 2002–2026 · 7 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π Interdisciplinary Bridge π§ Keyword Pioneer πΊοΈ Taxonomy Completionist (12) π Conference Polyglot (7)
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Academic Marathon
(22)
πΊοΈ
Taxonomy Completionist
(12)
π§
Keyword Pioneer
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Keyword Trendsetter Combo
(5)
π¬
Deep Specialist
(11)
π±
Topic Pioneer
π
Keyword Champion
π
Century Club
(27)
π
Conference Pioneer
π
Trend Setter
β
The Questioner
(2)
ποΈ
Keyword Collector
(116)
Conferences
NIPS (8)
COLT (7)
ALT (5)
ICML (3)
JMLR (3)
AISTATS (2)
UAI (1)
Top co-authors
Research topics
Keywords
distribution learning
(5)
sample complexity
(5)
k-means clustering
(4)
clustering algorithm
(4)
pac learning
(3)
empirical risk minimization
(3)
learning theory
(3)
semi-supervised learning
(2)
littlestone dimension
(2)
probabilistic lipschitzness
(2)
online learning
(2)
active learning
(2)
hypothesis class
(2)
semi-supervised clustering
(2)
vc dimension
(2)
multiclass classification
(2)
sample compression
(2)
hierarchical clustering
(2)
generalization bound
(2)
linkage-based algorithm
(2)
Papers
No Scale Sensitive Dimension for Distribution Learning
ALT 2026
A Novel Data-Dependent Learning Paradigm for Large Hypothesis Classes
ALT 2026
Inherent limitations of dimensions for characterizing learnability of distribution classes
COLT 2024
On Computable Online Learning
ALT 2023
Strategic Classification with Unknown User Manipulations
ICML 2023
Private Distribution Learning with Public Data: The View from Sample Compression
NIPS 2023
Distribution Learnability and Robustness
NIPS 2023
Identifying regions of trusted predictions
UAI 2021
Open Problem: Are all VC-classes CPAC learnable?
COLT 2021
On Learnability wih Computable Learners
ALT 2020
Semi-supervised clustering for de-duplication
AISTATS 2019
When can unlabeled data improve the learning rate?
COLT 2019
Multi-task {K}ernel {L}earning Based on {P}robabilistic {L}ipschitzness
ALT 2018
Nearly tight sample complexity bounds for learning mixtures of Gaussians via sample compression schemes
NIPS 2018
Empirical Risk Minimization Under Fairness Constraints
NIPS 2018
A Characterization of Linkage-Based Hierarchical Clustering
JMLR 2016
Clustering with Same-Cluster Queries
NIPS 2016
Hierarchical Label Queries with Data-Dependent Partitions
COLT 2015
Multiclass Learnability and the ERM Principle
JMLR 2015
The sample complexity of agnostic learning under deterministic labels
COLT 2014
Clustering in the Presence of Background Noise
ICML 2014
PLAL: Cluster-based active learning
COLT 2013
Clustering Oligarchies
AISTATS 2013
Monochromatic Bi-Clustering
ICML 2013
Multiclass Learnability and the ERM principle
COLT 2011
Towards Property-Based Classification of Clustering Paradigms
NIPS 2010
Measures of Clustering Quality: A Working Set of Axioms for Clustering
NIPS 2008
Analysis of Representations for Domain Adaptation
NIPS 2006
Limitations of Learning Via Embeddings in Euclidean Half Spaces
JMLR 2002