Souslin trees and successors of singular cardinals. - Shai Ben-David; Saharon Shelah (Ann. Pure Appl. Log., 1986)

The Weak □* is Really Weaker than the Full □. - Shai Ben-David; Menachem Magidor (J. Symb. Log., 1986)

תכונות קומבינטוריות של מונים עוקבים לסינגולריים (Combinatorial properties of successors of singular Cardinals.). - Shai Ben-David (1986)

The Global Time Assumption and Semantics for Concurrent Systems. - Shai Ben-David (PODC, 1988)

On the Theory of Average Case Complexity (abstract). - Shai Ben-David; Benny Chor; Oded Goldreich 001; Michael Luby (SCT, 1989)

A Parametrization Scheme for Classifying Models of Learnability. - Shai Ben-David; Gyora M. Benedek; Yishay Mansour (COLT, 1989)

On the Power of Randomization in Online Algorithms (Extended Abstract) - Shai Ben-David; Allan Borodin; Richard M. Karp; Gábor Tardos; Avi Wigderson (STOC, 1990)

On the Limitation of the Global Time Assumption in Distributed Systems (Extended Abstract). - Uri Abraham; Shai Ben-David; Shlomo Moran (WDAG, 1991)

Characterizations of Learnability for Classes of {O, ..., n}-Valued Functions. - Shai Ben-David; Nicolò Cesa-Bianchi; Philip M. Long (COLT, 1992)

Can Finite Samples Detect Singularities of Real-Valued Functions? - Shai Ben-David (STOC, 1992)

On the Theory of Average Case Complexity. - Shai Ben-David; Benny Chor; Oded Goldreich 001; Michael Luby (J. Comput. Syst. Sci., 1992)

On Learning in the Limit and Non-Uniform (epsilon, delta)-Learning. - Shai Ben-David; Michal Jacovi (COLT, 1993)

Applying VC-Dimension Analysis To 3D Object Recognition from Perspective Projections. - Michael Lindenbaum; Shai Ben-David (AAAI, 1994)

Learnability with Restricted Focus of Attention guarantees Noise-Tolerance. - Shai Ben-David; Eli Dichterman (AII/ALT, 1994)

On Ultrafilters and NP. - Shai Ben-David; Mauricio Karchmer; Eyal Kushilevitz (SCT, 1994)

Applying VC-dimension Analysis To Object Recognition. - Michael Lindenbaum; Shai Ben-David (ECCV (1), 1994)

A New Measure for the Study of On-Line Algorithms. - Shai Ben-David; Allan Borodin (Algorithmica, 1994)

On the Power of Randomization in On-Line Algorithms. - Shai Ben-David; Allan Borodin; Richard M. Karp; Gábor Tardos; Avi Wigderson (Algorithmica, 1994)

On Self-Directed Learning. - Shai Ben-David; Nadav Eiron; Eyal Kushilevitz (COLT, 1995)

A Note on VC-Dimension and Measures of Sets of Reals. - Shai Ben-David; Leonid Gurvits (COLT, 1995)

Characterizations of Learnability for Classes of {0, ..., n}-Valued Functions. - Shai Ben-David; Nicolò Cesa-Bianchi; David Haussler; Philip M. Long (J. Comput. Syst. Sci., 1995)

Learning by Distances - Shai Ben-David; Alon Itai; Eyal Kushilevitz (Inf. Comput., 1995)

A Parametrization Scheme for Classifying Models of PAC Learnability - Shai Ben-David; Gyora M. Benedek; Yishay Mansour (Inf. Comput., 1995)

A Composition Theorem for Learning Algorithms with Applications to Geometric Concept Classes - Shai Ben-David; Nader H. Bshouty; Eyal Kushilevitz (Electron. Colloquium Comput. Complex., 1996)

Scale-sensitive dimensions, uniform convergence, and learnability. - Noga Alon; Shai Ben-David; Nicolò Cesa-Bianchi; David Haussler (J. ACM, 1997)

Learning Distributions by Their Density Levels: A Paradigm for Learning without a Teacher. - Shai Ben-David; Michael Lindenbaum (J. Comput. Syst. Sci., 1997)

Online Learning versus Offline Learning. - Shai Ben-David; Eyal Kushilevitz; Yishay Mansour (Mach. Learn., 1997)

Can Finite Samples Detect Singularities of Reao-Valued Functions? - Shai Ben-David (Algorithmica, 1998)

Combinatorial Variability of Vapnik-chervonenkis Classes with Applications to Sample Compression Schemes. - Shai Ben-David; Ami Litman (Discret. Appl. Math., 1998)

On the Existence of Propositional Proof Systems and Oracle-relativized Propositional Logic. - Shai Ben-David; Anna Gringauze (Electron. Colloquium Comput. Complex., 1998)

Learning with Restricted Focus of Attention. - Shai Ben-David; Eli Dichterman (J. Comput. Syst. Sci., 1998)

Self-Directed Learning and Its Relation to the VC-Dimension and to Teacher-Directed Learning. - Shai Ben-David; Nadav Eiron (Mach. Learn., 1998)

Localization vs. Identification of Semi-Algebraic Sets. - Shai Ben-David; Michael Lindenbaum (Mach. Learn., 1998)

VC-Dimension Analysis of Object Recognition Tasks. - Michael Lindenbaum; Shai Ben-David (J. Math. Imaging Vis., 1999)

Localized Boosting. - Ron Meir; Ran El-Yaniv; Shai Ben-David (COLT, 2000)

Efficient Learning of Linear Perceptrons. - Shai Ben-David; Hans Ulrich Simon (NIPS, 2000)

A modal logic for subjective default reasoning. - Shai Ben-David; Rachel Ben-Eliyahu-Zohary (Artif. Intell., 2000)

A Note On Vc-Dimension And Measure Of Sets Of Reals. - Shai Ben-David; Leonid Gurvits (Comb. Probab. Comput., 2000)

A Note on Non-complete Problems in NPImage. - Shai Ben-David; Klaus Meer; Christian Michaux (J. Complex., 2000)

Learning Changing Concepts by Exploiting the Structure of Change. - Peter L. Bartlett; Shai Ben-David; Sanjeev R. Kulkarni (Mach. Learn., 2000)

Agnostic Boosting. - Shai Ben-David; Philip M. Long; Yishay Mansour (COLT/EuroCOLT, 2001)

A theoretical framework for learning from a pool of disparate data sources. - Shai Ben-David; Johannes Gehrke; Reba Schuller (KDD, 2002)

The Computational Complexity of Densest Region Detection. - Shai Ben-David; Nadav Eiron; Hans Ulrich Simon (J. Comput. Syst. Sci., 2002)

Limitations of Learning Via Embeddings in Euclidean Half Spaces. - Shai Ben-David; Nadav Eiron; Hans Ulrich Simon (J. Mach. Learn. Res., 2002)

Hardness results for neural network approximation problems. - Peter L. Bartlett; Shai Ben-David (Theor. Comput. Sci., 2002)

Exploiting Task Relatedness for Mulitple Task Learning. - Shai Ben-David; Reba Schuller (COLT, 2003)

On the difficulty of approximately maximizing agreements. - Shai Ben-David; Nadav Eiron; Philip M. Long (J. Comput. Syst. Sci., 2003)

A Framework for Statistical Clustering with a Constant Time Approximation Algorithms for K-Median Clustering. - Shai Ben-David (COLT, 2004)

Detecting Change in Data Streams. - Daniel Kifer; Shai Ben-David; Johannes Gehrke (VLDB, 2004)

Nonparametric change detection in 2D random sensor field. - Ting He 001; Shai Ben-David; Lang Tong 001 (ICASSP (4), 2005)

A Sober Look at Clustering Stability. - Shai Ben-David; Ulrike von Luxburg; Dávid Pál (COLT, 2006)

Learning Bounds for Support Vector Machines with Learned Kernels. - Nathan Srebro; Shai Ben-David (COLT, 2006)

Analysis of Representations for Domain Adaptation. - Shai Ben-David; John Blitzer; Koby Crammer; Fernando Pereira 003 (NIPS, 2006)

Alternative Measures of Computational Complexity with Applications to Agnostic Learning. - Shai Ben-David (TAMC, 2006)

Estimation of the number of operating sensors in large-scale sensor networks with mobile access. - Cristian Budianu; Shai Ben-David; Lang Tong 001 (IEEE Trans. Signal Process., 2006)

Nonparametric change detection and estimation in large-scale sensor networks. - Ting He 001; Shai Ben-David; Lang Tong 001 (IEEE Trans. Signal Process., 2006)

Stability of k -Means Clustering. - Shai Ben-David; Dávid Pál; Hans Ulrich Simon (COLT, 2007)

A framework for statistical clustering with constant time approximation algorithms for K-median and K-means clustering. - Shai Ben-David (Mach. Learn., 2007)

Foreword. - Shai Ben-David; John Case; Thomas Zeugmann (Theor. Comput. Sci., 2007)

Relating Clustering Stability to Properties of Cluster Boundaries. - Shai Ben-David; Ulrike von Luxburg (COLT, 2008)

Does Unlabeled Data Provably Help? Worst-case Analysis of the Sample Complexity of Semi-Supervised Learning. - Shai Ben-David; Tyler Lu; Dávid Pál (COLT, 2008)

Measures of Clustering Quality: A Working Set of Axioms for Clustering. - Shai Ben-David; Margareta Ackerman (NIPS, 2008)

A notion of task relatedness yielding provable multiple-task learning guarantees. - Shai Ben-David; Reba Schuller Borbely (Mach. Learn., 2008)

Agnostic Online Learning. - Shai Ben-David; Dávid Pál; Shai Shalev-Shwartz (COLT, 2009)

RTTS: towards enterprise-level real-time speech transcription and translation services. - Juan M. Huerta; Cheng Wu; Andrej Sakrajda; Sasha Caskey; Ea-Ee Jan; Alexander Faisman; Shai Ben-David; Wen Liu; Antonio Lee; Osamuyimen Stewart; Michael Frissora; David M. Lubensky (INTERSPEECH, 2009)

Theory-Practice Interplay in Machine Learning - Emerging Theoretical Challenges. - Shai Ben-David (ECML/PKDD (1), 2009)

A Uniqueness Theorem for Clustering. - Reza Zadeh; Shai Ben-David (UAI, 2009)

Clusterability: A Theoretical Study. - Margareta Ackerman; Shai Ben-David (AISTATS, 2009)

Learning Low Density Separators. - Shai Ben-David; Tyler Lu; Dávid Pál; Miroslava Sotáková (AISTATS, 2009)

Modeling and Querying Possible Repairs in Duplicate Detection. - George Beskales; Mohamed A. Soliman; Ihab F. Ilyas; Shai Ben-David (Proc. VLDB Endow., 2009)

Characterization of Linkage-based Clustering. - Margareta Ackerman; Shai Ben-David; David Loker (COLT, 2010)

ProbClean: A probabilistic duplicate detection system. - George Beskales; Mohamed A. Soliman; Ihab F. Ilyas; Shai Ben-David; Yubin Kim 001 (ICDE, 2010)

Towards Property-Based Classification of Clustering Paradigms. - Margareta Ackerman; Shai Ben-David; David Loker (NIPS, 2010)

Impossibility Theorems for Domain Adaptation. - Shai Ben-David; Tyler Lu; Teresa Luu; Dávid Pál (AISTATS, 2010)

A theory of learning from different domains. - Shai Ben-David; John Blitzer; Koby Crammer; Alex Kulesza; Fernando Pereira 003; Jennifer Wortman Vaughan (Mach. Learn., 2010)

Learning a Classifier when the Labeling Is Known. - Shalev Ben-David; Shai Ben-David (ALT, 2011)

Access to Unlabeled Data can Speed up Prediction Time. - Ruth Urner; Shai Shalev-Shwartz; Shai Ben-David (ICML, 2011)

Discerning Linkage-Based Algorithms among Hierarchical Clustering Methods. - Margareta Ackerman; Shai Ben-David (IJCAI, 2011)

Multiclass Learnability and the ERM principle. - Amit Daniely; Sivan Sabato; Shai Ben-David; Shai Shalev-Shwartz (COLT, 2011)

Weighted Clustering. - Margareta Ackerman; Shai Ben-David; Simina Brânzei; David Loker (AAAI, 2012)

On the Hardness of Domain Adaptation and the Utility of Unlabeled Target Samples. - Shai Ben-David; Ruth Urner (ALT, 2012)

Minimizing The Misclassification Error Rate Using a Surrogate Convex Loss. - Shai Ben-David; David Loker; Nathan Srebro; Karthik Sridharan (ICML, 2012)

Domain Adaptation–Can Quantity compensate for Quality?. - Shai Ben-David; Shai Shalev-Shwartz; Ruth Urner (ISAIM, 2012)

Theoretical analysis of domain adaptation - current state of the art. - Shai Ben-David (MLSLP, 2012)

Learning from Weak Teachers. - Ruth Urner; Shai Ben-David; Ohad Shamir (AISTATS, 2012)

Clustering Oligarchies. - Margareta Ackerman; Shai Ben-David; David Loker; Sivan Sabato (AISTATS, 2013)

PLAL: Cluster-based active learning. - Ruth Urner; Sharon Wulff; Shai Ben-David (COLT, 2013)

Monochromatic Bi-Clustering. - Sharon Wulff; Ruth Urner; Shai Ben-David (ICML (2), 2013)

A theoretical approach to the clustering selection problem. - Shai Ben-David (MultiClust@KDD, 2013)

Understanding Machine Learning - From Theory to Algorithms. - Shai Shalev-Shwartz; Shai Ben-David (Cambridge University Press, 2014)

The sample complexity of agnostic learning under deterministic labels. - Shai Ben-David; Ruth Urner (COLT, 2014)

Clustering in the Presence of Background Noise. - Shai Ben-David; Nika Haghtalab (ICML, 2014)

The sample complexity of agnostic learning with deterministic labels. - Shai Ben-David; Ruth Urner (ISAIM, 2014)

Domain adaptation-can quantity compensate for quality? - Shai Ben-David; Ruth Urner (Ann. Math. Artif. Intell., 2014)

Information Preserving Dimensionality Reduction. - Shrinu Kushagra; Shai Ben-David (ALT, 2015)

Multi-task and Lifelong Learning of Kernels. - Anastasia Pentina; Shai Ben-David (ALT, 2015)

Hierarchical Label Queries with Data-Dependent Partitions. - Samory Kpotufe; Ruth Urner; Shai Ben-David (COLT, 2015)

Representation Learning for Clustering: A Statistical Framework. - Hassan Ashtiani; Shai Ben-David (UAI, 2015)

Computational Feasibility of Clustering under Clusterability Assumptions. - Shai Ben-David (CoRR, 2015)

2 Notes on Classes with Vapnik-Chervonenkis Dimension 1. - Shai Ben-David (CoRR, 2015)

Clustering is Easy When ....What? - Shai Ben-David (CoRR, 2015)

On Version Space Compression. - Shai Ben-David; Ruth Urner (ALT, 2016)

Finding Meaningful Cluster Structure Amidst Background Noise. - Shrinu Kushagra; Samira Samadi; Shai Ben-David (ALT, 2016)

How Far Are We From Having a Satisfactory Theory of Clustering? - Shai Ben-David (MFCS, 2016)

Clustering with Same-Cluster Queries. - Hassan Ashtiani; Shrinu Kushagra; Shai Ben-David (NIPS, 2016)

Foundations of Unsupervised Learning (Dagstuhl Seminar 16382). - Maria-Florina Balcan; Shai Ben-David; Ruth Urner; Ulrike von Luxburg (Dagstuhl Reports, 2016)

A Characterization of Linkage-Based Hierarchical Clustering. - Margareta Ackerman; Shai Ben-David (J. Mach. Learn. Res., 2016)

Agnostic Distribution Learning via Compression. - Hassan Ashtiani; Shai Ben-David; Abbas Mehrabian (CoRR, 2017)

A learning problem that is independent of the set theory ZFC axioms. - Shai Ben-David; Pavel Hrubes; Shay Moran; Amir Shpilka; Amir Yehudayoff (CoRR, 2017)

Provably noise-robust, regularised k-means clustering. - Shrinu Kushagra; Nicole McNabb; Yaoliang Yu; Shai Ben-David (CoRR, 2017)

Sample-Efficient Learning of Mixtures. - Hassan Ashtiani; Shai Ben-David; Abbas Mehrabian (AAAI, 2018)

Clustering - What Both Theoreticians and Practitioners Are Doing Wrong. - Shai Ben-David (AAAI, 2018)

Multi-task {K}ernel {L}earning Based on {P}robabilistic {L}ipschitzness. - Anastasia Pentina; Shai Ben-David (ALT, 2018)

Nearly tight sample complexity bounds for learning mixtures of Gaussians via sample compression schemes. - Hassan Ashtiani; Shai Ben-David; Nicholas J. A. Harvey; Christopher Liaw; Abbas Mehrabian; Yaniv Plan (NeurIPS, 2018)

Empirical Risk Minimization Under Fairness Constraints. - Michele Donini; Luca Oneto; Shai Ben-David; John Shawe-Taylor; Massimiliano Pontil (NeurIPS, 2018)

Semi-supervised clustering for de-duplication. - Shrinu Kushagra; Shai Ben-David; Ihab F. Ilyas (AISTATS, 2019)

When can unlabeled data improve the learning rate? - Christina Göpfert; Shai Ben-David; Olivier Bousquet; Sylvain Gelly; Ilya O. Tolstikhin; Ruth Urner (COLT, 2019)

A Semi-Supervised Framework of Clustering Selection for De-Duplication. - Shrinu Kushagra; Hemant Saxena; Ihab F. Ilyas; Shai Ben-David (ICDE, 2019)

Learnability can be undecidable. - Shai Ben-David; Pavel Hrubes; Shay Moran; Amir Shpilka; Amir Yehudayoff (Nat. Mach. Intell., 2019)

Author Correction: Learnability can be undecidable. - Shai Ben-David; Pavel Hrubes; Shay Moran; Amir Shpilka; Amir Yehudayoff (Nat. Mach. Intell., 2019)

On Learnability wih Computable Learners. - Sushant Agarwal; Nivasini Ananthakrishnan; Shai Ben-David; Tosca Lechner; Ruth Urner (ALT, 2020)

Enforcing Interpretability and its Statistical Impacts: Trade-offs between Accuracy and Interpretability. - Gintare Karolina Dziugaite; Shai Ben-David; Daniel M. Roy 001 (CoRR, 2020)

Near-optimal Sample Complexity Bounds for Robust Learning of Gaussian Mixtures via Compression Schemes. - Hassan Ashtiani; Shai Ben-David; Nicholas J. A. Harvey; Christopher Liaw; Abbas Mehrabian; Yaniv Plan (J. ACM, 2020)

Classification Confidence Scores with Point-wise Guarantees. - Nivasini Ananthakrishnan; Shai Ben-David; Tosca Lechner (SafeAI@AAAI, 2021)

Open Problem: Are all VC-classes CPAC learnable? - Sushant Agarwal; Nivasini Ananthakrishnan; Shai Ben-David; Tosca Lechner; Ruth Urner (COLT, 2021)

Learnability can be independent of set theory (invited paper). - Shai Ben-David; Pavel Hrubes; Shay Moran; Amir Shpilka; Amir Yehudayoff (STOC, 2021)

Identifying regions of trusted predictions. - Nivasini Ananthakrishnan; Shai Ben-David; Tosca Lechner; Ruth Urner (UAI, 2021)

Impossibility results for fair representations. - Tosca Lechner; Shai Ben-David; Sushant Agarwal; Nivasini Ananthakrishnan (CoRR, 2021)

Weighted clustering: Towards solving the user's dilemma. - Margareta Ackerman; Shai Ben-David; Simina Brânzei; David Loker (Pattern Recognit., 2021)

Inherent Limitations of Multi-Task Fair Representations. - Tosca Lechner; Shai Ben-David (CoLLAs, 2022)

On Computable Online Learning. - Niki Hasrati; Shai Ben-David (ALT, 2023)

Strategic Classification with Unknown User Manipulations. - Tosca Lechner; Ruth Urner; Shai Ben-David (ICML, 2023)

Distribution Learnability and Robustness. - Shai Ben-David; Alex Bie; Gautam Kamath 001; Tosca Lechner (NeurIPS, 2023)

Private Distribution Learning with Public Data: The View from Sample Compression. - Shai Ben-David; Alex Bie; Clément L. Canonne; Gautam Kamath 001; Vikrant Singhal (NeurIPS, 2023)

Impossibility of Characterizing Distribution Learning - a simple solution to a long-standing problem. - Tosca Lechner; Shai Ben-David (CoRR, 2023)

Inherent limitations of dimensions for characterizing learnability of distribution classes. - Tosca Lechner; Shai Ben-David (COLT, 2024)

Continual Learning: Applications and the Road Forward. - Eli Verwimp; Rahaf Aljundi; Shai Ben-David; Matthias Bethge; Andrea Cossu; Alexander Gepperth; Tyler L. Hayes; Eyke Hüllermeier; Christopher Kanan; Dhireesha Kudithipudi; Christoph H. Lampert; Martin Mundt; et al. (Trans. Mach. Learn. Res., 2024)

Learning from positive and unlabeled examples -Finite size sample bounds. - Farnam Mansouri; Shai Ben-David (CoRR, 2025)