Shai Ben-David

176 papers A* 54A 10B 11C 1Misc 2Journal 73Unranked 22

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Active learning from positive and unlabeled examples. CoRR Farnam Mansouri, Sandra Zilles, Shai Ben-David
2026	J	`jnl`	Learning with Multiple Correct Answers - A Trichotomy of Regret Bounds under Different Feedback Models. CoRR Alireza F. Pour, Farnam Mansouri, Shai Ben-David
2026	J	`jnl`	Online Learning with Improving Agents: Multiclass, Budgeted Agents and Bandit Learners. CoRR Sajad Ashkezari, Shai Ben-David
2025	J	`jnl`	A Novel Data-Dependent Learning Paradigm for Large Hypothesis Classes. CoRR Alireza F. Pour, Shai Ben-David
2025	J	`jnl`	Learning from positive and unlabeled examples -Finite size sample bounds. CoRR Farnam Mansouri, Shai Ben-David
2024	J	`jnl`	Continual Learning: Applications and the Road Forward. Trans. Mach. Learn. Res. 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, Razvan Pascanu, Adrian Popescu, Andreas S. Tolias, Joost van de Weijer, Bing Liu, Vincenzo Lomonaco, Tinne Tuytelaars, Gido M. van de Ven
2024	J	`jnl`	Distribution Learnability and Robustness. CoRR Shai Ben-David, Alex Bie, Gautam Kamath, Tosca Lechner
2024	A*	`conf`	Inherent limitations of dimensions for characterizing learnability of distribution classes. COLT Tosca Lechner, Shai Ben-David
2023	J	`jnl`	Continual Learning: Applications and the Road Forward. CoRR 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, Razvan Pascanu, Adrian Popescu, Andreas S. Tolias, Joost van de Weijer, Bing Liu, Vincenzo Lomonaco, Tinne Tuytelaars, Gido M. van de Ven
2023	A*	`conf`	Distribution Learnability and Robustness. NeurIPS Shai Ben-David, Alex Bie, Gautam Kamath, Tosca Lechner
2023	J	`jnl`	Impossibility of Characterizing Distribution Learning - a simple solution to a long-standing problem. CoRR Tosca Lechner, Shai Ben-David
2023	B	`conf`	On Computable Online Learning. ALT Niki Hasrati, Shai Ben-David
2023	J	`jnl`	On Computable Online Learning. CoRR Niki Hasrati, Shai Ben-David
2023	A*	`conf`	Private Distribution Learning with Public Data: The View from Sample Compression. NeurIPS Shai Ben-David, Alex Bie, Clément L. Canonne, Gautam Kamath, Vikrant Singhal
2023	J	`jnl`	Private Distribution Learning with Public Data: The View from Sample Compression. CoRR Shai Ben-David, Alex Bie, Clément L. Canonne, Gautam Kamath, Vikrant Singhal
2023	A*	`conf`	Strategic Classification with Unknown User Manipulations. ICML Tosca Lechner, Ruth Urner, Shai Ben-David
2022	—	`conf`	Inherent Limitations of Multi-Task Fair Representations. CoLLAs Tosca Lechner, Shai Ben-David
2021	—	`conf`	Classification Confidence Scores with Point-wise Guarantees. SafeAI@AAAI Nivasini Ananthakrishnan, Shai Ben-David, Tosca Lechner
2021	A	`conf`	Identifying regions of trusted predictions. UAI Nivasini Ananthakrishnan, Shai Ben-David, Tosca Lechner, Ruth Urner
2021	J	`jnl`	Impossibility results for fair representations. CoRR Tosca Lechner, Shai Ben-David, Sushant Agarwal, Nivasini Ananthakrishnan
2021	A*	`conf`	Learnability can be independent of set theory (invited paper). STOC Shai Ben-David, Pavel Hrubes, Shay Moran, Amir Shpilka, Amir Yehudayoff
2021	A*	`conf`	Open Problem: Are all VC-classes CPAC learnable? COLT Sushant Agarwal, Nivasini Ananthakrishnan, Shai Ben-David, Tosca Lechner, Ruth Urner
2021	J	`jnl`	Weighted clustering: Towards solving the user's dilemma. Pattern Recognit. Margareta Ackerman, Shai Ben-David, Simina Brânzei, David Loker
2020	J	`jnl`	Enforcing Interpretability and its Statistical Impacts: Trade-offs between Accuracy and Interpretability. CoRR Gintare Karolina Dziugaite, Shai Ben-David, Daniel M. Roy
2020	J	`jnl`	Near-optimal Sample Complexity Bounds for Robust Learning of Gaussian Mixtures via Compression Schemes. J. ACM Hassan Ashtiani, Shai Ben-David, Nicholas J. A. Harvey, Christopher Liaw, Abbas Mehrabian, Yaniv Plan
2020	B	`conf`	On Learnability wih Computable Learners. ALT Sushant Agarwal, Nivasini Ananthakrishnan, Shai Ben-David, Tosca Lechner, Ruth Urner
2019	A*	`conf`	A Semi-Supervised Framework of Clustering Selection for De-Duplication. ICDE Shrinu Kushagra, Hemant Saxena, Ihab F. Ilyas, Shai Ben-David
2019	J	`jnl`	Author Correction: Learnability can be undecidable. Nat. Mach. Intell. Shai Ben-David, Pavel Hrubes, Shay Moran, Amir Shpilka, Amir Yehudayoff
2019	J	`jnl`	Learnability can be undecidable. Nat. Mach. Intell. Shai Ben-David, Pavel Hrubes, Shay Moran, Amir Shpilka, Amir Yehudayoff
2019	A	`conf`	Semi-supervised clustering for de-duplication. AISTATS Shrinu Kushagra, Shai Ben-David, Ihab F. Ilyas
2019	A*	`conf`	When can unlabeled data improve the learning rate? COLT Christina Göpfert, Shai Ben-David, Olivier Bousquet, Sylvain Gelly, Ilya O. Tolstikhin, Ruth Urner
2019	J	`jnl`	When can unlabeled data improve the learning rate? CoRR Christina Göpfert, Shai Ben-David, Olivier Bousquet, Sylvain Gelly, Ilya O. Tolstikhin, Ruth Urner
2018	A*	`conf`	Clustering - What Both Theoreticians and Practitioners Are Doing Wrong. AAAI Shai Ben-David
2018	J	`jnl`	Clustering - What Both Theoreticians and Practitioners are Doing Wrong. CoRR Shai Ben-David
2018	A*	`conf`	Empirical Risk Minimization Under Fairness Constraints. NeurIPS Michele Donini, Luca Oneto, Shai Ben-David, John Shawe-Taylor, Massimiliano Pontil
2018	J	`jnl`	Empirical Risk Minimization under Fairness Constraints. CoRR Michele Donini, Luca Oneto, Shai Ben-David, John Shawe-Taylor, Massimiliano Pontil
2018	B	`conf`	Multi-task {K}ernel {L}earning Based on {P}robabilistic {L}ipschitzness. ALT Anastasia Pentina, Shai Ben-David
2018	A*	`conf`	Nearly tight sample complexity bounds for learning mixtures of Gaussians via sample compression schemes. NeurIPS Hassan Ashtiani, Shai Ben-David, Nicholas J. A. Harvey, Christopher Liaw, Abbas Mehrabian, Yaniv Plan
2018	A*	`conf`	Sample-Efficient Learning of Mixtures. AAAI Hassan Ashtiani, Shai Ben-David, Abbas Mehrabian
2018	J	`jnl`	Semi-supervised clustering for de-duplication. CoRR Shrinu Kushagra, Shai Ben-David, Ihab F. Ilyas
2017	J	`jnl`	A learning problem that is independent of the set theory ZFC axioms. CoRR Shai Ben-David, Pavel Hrubes, Shay Moran, Amir Shpilka, Amir Yehudayoff
2017	J	`jnl`	Agnostic Distribution Learning via Compression. CoRR Hassan Ashtiani, Shai Ben-David, Abbas Mehrabian
2017	J	`jnl`	Provably noise-robust, regularised k-means clustering. CoRR Shrinu Kushagra, Nicole McNabb, Yaoliang Yu, Shai Ben-David
2017	J	`jnl`	Sample-Efficient Learning of Mixtures. CoRR Hassan Ashtiani, Shai Ben-David, Abbas Mehrabian
2016	J	`jnl`	A Characterization of Linkage-Based Hierarchical Clustering. J. Mach. Learn. Res. Margareta Ackerman, Shai Ben-David
2016	—	`conf`	Clustering with Same-Cluster Queries. NIPS Hassan Ashtiani, Shrinu Kushagra, Shai Ben-David
2016	J	`jnl`	Clustering with Same-Cluster Queries. CoRR Hassan Ashtiani, Shrinu Kushagra, Shai Ben-David
2016	B	`conf`	Finding Meaningful Cluster Structure Amidst Background Noise. ALT Shrinu Kushagra, Samira Samadi, Shai Ben-David
2016	J	`jnl`	Foundations of Unsupervised Learning (Dagstuhl Seminar 16382). Dagstuhl Reports Maria-Florina Balcan, Shai Ben-David, Ruth Urner, Ulrike von Luxburg
2016	B	`conf`	How Far Are We From Having a Satisfactory Theory of Clustering? MFCS Shai Ben-David
2016	J	`jnl`	Multi-task and Lifelong Learning of Kernels. CoRR Anastasia Pentina, Shai Ben-David
2016	B	`conf`	On Version Space Compression. ALT Shai Ben-David, Ruth Urner
2015	J	`jnl`	2 Notes on Classes with Vapnik-Chervonenkis Dimension 1. CoRR Shai Ben-David
2015	J	`jnl`	Clustering is Easy When ....What? CoRR Shai Ben-David
2015	J	`jnl`	Computational Feasibility of Clustering under Clusterability Assumptions. CoRR Shai Ben-David
2015	A*	`conf`	Hierarchical Label Queries with Data-Dependent Partitions. COLT Samory Kpotufe, Ruth Urner, Shai Ben-David
2015	B	`conf`	Information Preserving Dimensionality Reduction. ALT Shrinu Kushagra, Shai Ben-David
2015	B	`conf`	Multi-task and Lifelong Learning of Kernels. ALT Anastasia Pentina, Shai Ben-David
2015	J	`jnl`	Multiclass learnability and the ERM principle. J. Mach. Learn. Res. Amit Daniely, Sivan Sabato, Shai Ben-David, Shai Shalev-Shwartz
2015	A	`conf`	Representation Learning for Clustering: A Statistical Framework. UAI Hassan Ashtiani, Shai Ben-David
2015	J	`jnl`	Representation Learning for Clustering: A Statistical Framework. CoRR Hassan Ashtiani, Shai Ben-David
2014	A*	`conf`	Clustering in the Presence of Background Noise. ICML Shai Ben-David, Nika Haghtalab
2014	J	`jnl`	Domain adaptation-can quantity compensate for quality? Ann. Math. Artif. Intell. Shai Ben-David, Ruth Urner
2014	A*	`conf`	The sample complexity of agnostic learning under deterministic labels. COLT Shai Ben-David, Ruth Urner
2014	Misc	`conf`	The sample complexity of agnostic learning with deterministic labels. ISAIM Shai Ben-David, Ruth Urner
2014	—	`book`	Understanding Machine Learning - From Theory to Algorithms. Shai Shalev-Shwartz, Shai Ben-David
2013	—	`conf`	A theoretical approach to the clustering selection problem. MultiClust@KDD Shai Ben-David
2013	A	`conf`	Clustering Oligarchies. AISTATS Margareta Ackerman, Shai Ben-David, David Loker, Sivan Sabato
2013	—	`conf`	Monochromatic Bi-Clustering. ICML (2) Sharon Wulff, Ruth Urner, Shai Ben-David
2013	J	`jnl`	Multiclass learnability and the ERM principle. CoRR Amit Daniely, Sivan Sabato, Shai Ben-David, Shai Shalev-Shwartz
2013	A*	`conf`	PLAL: Cluster-based active learning. COLT Ruth Urner, Sharon Wulff, Shai Ben-David
2012	J	`jnl`	A Uniqueness Theorem for Clustering CoRR Reza Bosagh Zadeh, Shai Ben-David
2012	Misc	`conf`	Domain Adaptation--Can Quantity compensate for Quality?. ISAIM Shai Ben-David, Shai Shalev-Shwartz, Ruth Urner
2012	A	`conf`	Learning from Weak Teachers. AISTATS Ruth Urner, Shai Ben-David, Ohad Shamir
2012	A*	`conf`	Minimizing The Misclassification Error Rate Using a Surrogate Convex Loss. ICML Shai Ben-David, David Loker, Nathan Srebro, Karthik Sridharan
2012	B	`conf`	On the Hardness of Domain Adaptation and the Utility of Unlabeled Target Samples. ALT Shai Ben-David, Ruth Urner
2012	—	`conf`	Theoretical analysis of domain adaptation - current state of the art. MLSLP Shai Ben-David
2012	A*	`conf`	Weighted Clustering. AAAI Margareta Ackerman, Shai Ben-David, Simina Brânzei, David Loker
2011	A*	`conf`	Access to Unlabeled Data can Speed up Prediction Time. ICML Ruth Urner, Shai Shalev-Shwartz, Shai Ben-David
2011	A*	`conf`	Discerning Linkage-Based Algorithms among Hierarchical Clustering Methods. IJCAI Margareta Ackerman, Shai Ben-David
2011	B	`conf`	Learning a Classifier when the Labeling Is Known. ALT Shalev Ben-David, Shai Ben-David
2011	A*	`conf`	Multiclass Learnability and the ERM principle. COLT Amit Daniely, Sivan Sabato, Shai Ben-David, Shai Shalev-Shwartz
2011	J	`jnl`	Weighted Clustering CoRR Margareta Ackerman, Shai Ben-David, Simina Brânzei, David Loker
2010	J	`jnl`	A theory of learning from different domains. Mach. Learn. Shai Ben-David, John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, Jennifer Wortman Vaughan
2010	A*	`conf`	Characterization of Linkage-based Clustering. COLT Margareta Ackerman, Shai Ben-David, David Loker
2010	A	`conf`	Impossibility Theorems for Domain Adaptation. AISTATS Shai Ben-David, Tyler Lu, Teresa Luu, Dávid Pál
2010	A*	`conf`	ProbClean: A probabilistic duplicate detection system. ICDE George Beskales, Mohamed A. Soliman, Ihab F. Ilyas, Shai Ben-David, Yubin Kim
2010	—	`conf`	Towards Property-Based Classification of Clustering Paradigms. NIPS Margareta Ackerman, Shai Ben-David, David Loker
2009	A	`conf`	A Uniqueness Theorem for Clustering. UAI Reza Zadeh, Shai Ben-David
2009	A*	`conf`	Agnostic Online Learning. COLT Shai Ben-David, Dávid Pál, Shai Shalev-Shwartz
2009	A	`conf`	Clusterability: A Theoretical Study. AISTATS Margareta Ackerman, Shai Ben-David
2009	A	`conf`	Learning Low Density Separators. AISTATS Shai Ben-David, Tyler Lu, Dávid Pál, Miroslava Sotáková
2009	J	`jnl`	Modeling and Querying Possible Repairs in Duplicate Detection. Proc. VLDB Endow. George Beskales, Mohamed A. Soliman, Ihab F. Ilyas, Shai Ben-David
2009	A	`conf`	RTTS: towards enterprise-level real-time speech transcription and translation services. INTERSPEECH 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
2009	—	`conf`	Theory-Practice Interplay in Machine Learning - Emerging Theoretical Challenges. ECML/PKDD (1) Shai Ben-David
2008	J	`jnl`	A notion of task relatedness yielding provable multiple-task learning guarantees. Mach. Learn. Shai Ben-David, Reba Schuller Borbely
2008	A*	`conf`	Does Unlabeled Data Provably Help? Worst-case Analysis of the Sample Complexity of Semi-Supervised Learning. COLT Shai Ben-David, Tyler Lu, Dávid Pál
2008	J	`jnl`	Learning Low-Density Separators CoRR Shai Ben-David, Tyler Lu, Dávid Pál, Miroslava Sotáková
2008	—	`conf`	Measures of Clustering Quality: A Working Set of Axioms for Clustering. NIPS Shai Ben-David, Margareta Ackerman
2008	A*	`conf`	Relating Clustering Stability to Properties of Cluster Boundaries. COLT Shai Ben-David, Ulrike von Luxburg
2007	J	`jnl`	A framework for statistical clustering with constant time approximation algorithms for Mach. Learn. Shai Ben-David
2007	J	`jnl`	Foreword. Theor. Comput. Sci. Shai Ben-David, John Case, Thomas Zeugmann
2007	A*	`conf`	Stability of COLT Shai Ben-David, Dávid Pál, Hans Ulrich Simon
2006	A*	`conf`	A Sober Look at Clustering Stability. COLT Shai Ben-David, Ulrike von Luxburg, Dávid Pál
2006	C	`conf`	Alternative Measures of Computational Complexity with Applications to Agnostic Learning. TAMC Shai Ben-David
2006	—	`conf`	Analysis of Representations for Domain Adaptation. NIPS Shai Ben-David, John Blitzer, Koby Crammer, Fernando Pereira
2006	J	`jnl`	Estimation of the number of operating sensors in large-scale sensor networks with mobile access. IEEE Trans. Signal Process. Cristian Budianu, Shai Ben-David, Lang Tong
2006	A*	`conf`	Learning Bounds for Support Vector Machines with Learned Kernels. COLT Nathan Srebro, Shai Ben-David
2006	J	`jnl`	Nonparametric change detection and estimation in large-scale sensor networks. IEEE Trans. Signal Process. Ting He, Shai Ben-David, Lang Tong
2005	—	`conf`	Nonparametric change detection in 2D random sensor field. ICASSP (4) Ting He, Shai Ben-David, Lang Tong
2004	A*	`conf`	A Framework for Statistical Clustering with a Constant Time Approximation Algorithms for K-Median Clustering. COLT Shai Ben-David
2004	B	`ed.`	Algorithmic Learning Theory, 15th International Conference, ALT 2004, Padova, Italy, October 2-5, 2004, Proceedings ALT Shai Ben-David, John Case, Akira Maruoka
2004	A*	`conf`	Detecting Change in Data Streams. VLDB Daniel Kifer, Shai Ben-David, Johannes Gehrke
2003	A*	`conf`	Exploiting Task Relatedness for Mulitple Task Learning. COLT Shai Ben-David, Reba Schuller
2003	J	`jnl`	On the difficulty of approximately maximizing agreements. J. Comput. Syst. Sci. Shai Ben-David, Nadav Eiron, Philip M. Long
2002	A*	`conf`	A theoretical framework for learning from a pool of disparate data sources. KDD Shai Ben-David, Johannes Gehrke, Reba Schuller
2002	J	`jnl`	Hardness results for neural network approximation problems. Theor. Comput. Sci. Peter L. Bartlett, Shai Ben-David
2002	J	`jnl`	Limitations of Learning Via Embeddings in Euclidean Half Spaces. J. Mach. Learn. Res. Shai Ben-David, Nadav Eiron, Hans Ulrich Simon
2002	J	`jnl`	The Computational Complexity of Densest Region Detection. J. Comput. Syst. Sci. Shai Ben-David, Nadav Eiron, Hans Ulrich Simon
2001	—	`conf`	Agnostic Boosting. COLT/EuroCOLT Shai Ben-David, Philip M. Long, Yishay Mansour
2001	—	`conf`	Limitations of Learning via Embeddings in Euclidean Half-Spaces. COLT/EuroCOLT Shai Ben-David, Nadav Eiron, Hans Ulrich Simon
2000	J	`jnl`	A Note On Vc-Dimension And Measure Of Sets Of Reals. Comb. Probab. Comput. Shai Ben-David, Leonid Gurvits
2000	J	`jnl`	A Note on Non-complete Problems in NPImage. J. Complex. Shai Ben-David, Klaus Meer, Christian Michaux
2000	J	`jnl`	A modal logic for subjective default reasoning. Artif. Intell. Shai Ben-David, Rachel Ben-Eliyahu-Zohary
2000	—	`conf`	Efficient Learning of Linear Perceptrons. NIPS Shai Ben-David, Hans Ulrich Simon
2000	J	`jnl`	Learning Changing Concepts by Exploiting the Structure of Change. Mach. Learn. Peter L. Bartlett, Shai Ben-David, Sanjeev R. Kulkarni
2000	A*	`conf`	Localized Boosting. COLT Ron Meir, Ran El-Yaniv, Shai Ben-David
2000	A*	`conf`	On the Difficulty of Approximately Maximizing Agreements. COLT Shai Ben-David, Nadav Eiron, Philip M. Long
2000	A*	`conf`	The Computational Complexity of Densest Region Detection. COLT Shai Ben-David, Nadav Eiron, Hans Ulrich Simon
1999	—	`conf`	Hardness Results for Neural Network Approximation Problems. EuroCOLT Peter L. Bartlett, Shai Ben-David
1999	A*	`ed.`	Proceedings of the Twelfth Annual Conference on Computational Learning Theory, COLT 1999, Santa Cruz, CA, USA, July 7-9, 1999 COLT Shai Ben-David, Philip M. Long
1999	J	`jnl`	VC-Dimension Analysis of Object Recognition Tasks. J. Math. Imaging Vis. Michael Lindenbaum, Shai Ben-David
1998	J	`jnl`	Can Finite Samples Detect Singularities of Reao-Valued Functions? Algorithmica Shai Ben-David
1998	J	`jnl`	Combinatorial Variability of Vapnik-chervonenkis Classes with Applications to Sample Compression Schemes. Discret. Appl. Math. Shai Ben-David, Ami Litman
1998	J	`jnl`	Learning with Restricted Focus of Attention. J. Comput. Syst. Sci. Shai Ben-David, Eli Dichterman
1998	J	`jnl`	Localization vs. Identification of Semi-Algebraic Sets. Mach. Learn. Shai Ben-David, Michael Lindenbaum
1998	J	`jnl`	On the Existence of Propositional Proof Systems and Oracle-relativized Propositional Logic. Electron. Colloquium Comput. Complex. Shai Ben-David, Anna Gringauze
1998	J	`jnl`	Self-Directed Learning and Its Relation to the VC-Dimension and to Teacher-Directed Learning. Mach. Learn. Shai Ben-David, Nadav Eiron
1997	A*	`conf`	A Composition Theorem for Learning Algorithms with Applications to Geometric Concept Classes. STOC Shai Ben-David, Nader H. Bshouty, Eyal Kushilevitz
1997	—	`ed.`	Computational Learning Theory, Third European Conference, EuroCOLT '97, Jerusalem, Israel, March 17-19, 1997, Proceedings EuroCOLT Shai Ben-David
1997	J	`jnl`	Learning Distributions by Their Density Levels: A Paradigm for Learning without a Teacher. J. Comput. Syst. Sci. Shai Ben-David, Michael Lindenbaum
1997	J	`jnl`	Online Learning versus Offline Learning. Mach. Learn. Shai Ben-David, Eyal Kushilevitz, Yishay Mansour
1997	J	`jnl`	Scale-sensitive dimensions, uniform convergence, and learnability. J. ACM Noga Alon, Shai Ben-David, Nicolò Cesa-Bianchi, David Haussler
1996	J	`jnl`	A Composition Theorem for Learning Algorithms with Applications to Geometric Concept Classes Electron. Colloquium Comput. Complex. Shai Ben-David, Nader H. Bshouty, Eyal Kushilevitz
1996	A*	`conf`	Learning Changing Concepts by Exploiting the Structure of Change. COLT Peter L. Bartlett, Shai Ben-David, Sanjeev R. Kulkarni
1995	A*	`conf`	A Note on VC-Dimension and Measures of Sets of Reals. COLT Shai Ben-David, Leonid Gurvits
1995	J	`jnl`	A Parametrization Scheme for Classifying Models of PAC Learnability Inf. Comput. Shai Ben-David, Gyora M. Benedek, Yishay Mansour
1995	J	`jnl`	Characterizations of Learnability for Classes of {0, ..., n}-Valued Functions. J. Comput. Syst. Sci. Shai Ben-David, Nicolò Cesa-Bianchi, David Haussler, Philip M. Long
1995	J	`jnl`	Learning by Distances Inf. Comput. Shai Ben-David, Alon Itai, Eyal Kushilevitz
1995	—	`conf`	Learning distributions by their density-levels - a paradigm for learning without a teacher. EuroCOLT Shai Ben-David, Michael Lindenbaum
1995	A*	`conf`	On Self-Directed Learning. COLT Shai Ben-David, Nadav Eiron, Eyal Kushilevitz
1995	—	`conf`	Online learning versus offline learning. EuroCOLT Shai Ben-David, Eyal Kushilevitz, Yishay Mansour
1994	J	`jnl`	A New Measure for the Study of On-Line Algorithms. Algorithmica Shai Ben-David, Allan Borodin
1994	A*	`conf`	Applying VC-Dimension Analysis To 3D Object Recognition from Perspective Projections. AAAI Michael Lindenbaum, Shai Ben-David
1994	—	`conf`	Applying VC-dimension Analysis To Object Recognition. ECCV (1) Michael Lindenbaum, Shai Ben-David
1994	—	`conf`	Learnability with Restricted Focus of Attention guarantees Noise-Tolerance. AII/ALT Shai Ben-David, Eli Dichterman
1994	—	`conf`	On Ultrafilters and NP. SCT Shai Ben-David, Mauricio Karchmer, Eyal Kushilevitz
1994	J	`jnl`	On the Power of Randomization in On-Line Algorithms. Algorithmica Shai Ben-David, Allan Borodin, Richard M. Karp, Gábor Tardos, Avi Wigderson
1994	A*	`conf`	a modal logic for subjective default reasoning LICS Shai Ben-David, Rachel Ben-Eliyahu
1993	A*	`conf`	Learning with Restricted Focus of Attention. COLT Shai Ben-David, Eli Dichterman
1993	A*	`conf`	Localization vs. Identification of Semi-Algebraic Sets. COLT Shai Ben-David, Michael Lindenbaum
1993	A*	`conf`	On Learning in the Limit and Non-Uniform (epsilon, delta)-Learning. COLT Shai Ben-David, Michal Jacovi
1993	A*	`conf`	Scale-sensitive Dimensions, Uniform Convergence, and Learnability FOCS Noga Alon, Shai Ben-David, Nicolò Cesa-Bianchi, David Haussler
1992	A*	`conf`	Can Finite Samples Detect Singularities of Real-Valued Functions? STOC Shai Ben-David
1992	A*	`conf`	Characterizations of Learnability for Classes of { COLT Shai Ben-David, Nicolò Cesa-Bianchi, Philip M. Long
1992	J	`jnl`	On the Theory of Average Case Complexity. J. Comput. Syst. Sci. Shai Ben-David, Benny Chor, Oded Goldreich, Michael Luby
1991	—	`conf`	On the Limitation of the Global Time Assumption in Distributed Systems (Extended Abstract). WDAG Uri Abraham, Shai Ben-David, Shlomo Moran
1990	A*	`conf`	Learning by Distances. COLT Shai Ben-David, Alon Itai, Eyal Kushilevitz
1990	A*	`conf`	On the Power of Randomization in Online Algorithms (Extended Abstract) STOC Shai Ben-David, Allan Borodin, Richard M. Karp, Gábor Tardos, Avi Wigderson
1989	A*	`conf`	A Parametrization Scheme for Classifying Models of Learnability. COLT Shai Ben-David, Gyora M. Benedek, Yishay Mansour
1989	A*	`conf`	On the Theory of Average Case Complexity STOC Shai Ben-David, Benny Chor, Oded Goldreich, Michael Luby
1989	—	`conf`	On the Theory of Average Case Complexity (abstract). SCT Shai Ben-David, Benny Chor, Oded Goldreich, Michael Luby
1988	A*	`conf`	The Global Time Assumption and Semantics for Concurrent Systems. PODC Shai Ben-David
1986	J	`jnl`	Souslin trees and successors of singular cardinals. Ann. Pure Appl. Log. Shai Ben-David, Saharon Shelah
1986	J	`jnl`	The Weak □* is Really Weaker than the Full □. J. Symb. Log. Shai Ben-David, Menachem Magidor
1986	—	`—`	תכונות קומבינטוריות של מונים עוקבים לסינגולריים (Combinatorial properties of successors of singular Cardinals.). Shai Ben-David