Shai Ben-David

According to our database1, Shai Ben-David authored at least 116 papers between 1986 and 2019.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of two.

Timeline

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Bibliography

2019
A Semi-Supervised Framework of Clustering Selection for De-Duplication.
Proceedings of the 35th IEEE International Conference on Data Engineering, 2019

When can unlabeled data improve the learning rate?
Proceedings of the Conference on Learning Theory, 2019

Semi-supervised clustering for de-duplication.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Empirical Risk Minimization Under Fairness Constraints.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Nearly tight sample complexity bounds for learning mixtures of Gaussians via sample compression schemes.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Multi-task {K}ernel {L}earning Based on {P}robabilistic {L}ipschitzness.
Proceedings of the Algorithmic Learning Theory, 2018

Clustering - What Both Theoreticians and Practitioners Are Doing Wrong.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Sample-Efficient Learning of Mixtures.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2016
A Characterization of Linkage-Based Hierarchical Clustering.
J. Mach. Learn. Res., 2016

Foundations of Unsupervised Learning (Dagstuhl Seminar 16382).
Dagstuhl Reports, 2016

Clustering with Same-Cluster Queries.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

How Far Are We From Having a Satisfactory Theory of Clustering?
Proceedings of the 41st International Symposium on Mathematical Foundations of Computer Science, 2016

Finding Meaningful Cluster Structure Amidst Background Noise.
Proceedings of the Algorithmic Learning Theory - 27th International Conference, 2016

On Version Space Compression.
Proceedings of the Algorithmic Learning Theory - 27th International Conference, 2016

2015
Representation Learning for Clustering: A Statistical Framework.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Hierarchical Label Queries with Data-Dependent Partitions.
Proceedings of The 28th Conference on Learning Theory, 2015

Multi-task and Lifelong Learning of Kernels.
Proceedings of the Algorithmic Learning Theory - 26th International Conference, 2015

Information Preserving Dimensionality Reduction.
Proceedings of the Algorithmic Learning Theory - 26th International Conference, 2015

2014
Domain adaptation-can quantity compensate for quality?
Ann. Math. Artif. Intell., 2014

The sample complexity of agnostic learning with deterministic labels.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2014

Clustering in the Presence of Background Noise.
Proceedings of the 31th International Conference on Machine Learning, 2014

The sample complexity of agnostic learning under deterministic labels.
Proceedings of The 27th Conference on Learning Theory, 2014

2013
A theoretical approach to the clustering selection problem.
Proceedings of the 4th MultiClust Workshop on Multiple Clusterings, 2013

Monochromatic Bi-Clustering.
Proceedings of the 30th International Conference on Machine Learning, 2013

PLAL: Cluster-based active learning.
Proceedings of the COLT 2013, 2013

Clustering Oligarchies.
Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012
Learning from Weak Teachers.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Theoretical analysis of domain adaptation - current state of the art.
Proceedings of the 2012 Symposium on Machine Learning in Speech and Language Processing, 2012

Domain Adaptation--Can Quantity compensate for Quality?.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2012

Minimizing The Misclassification Error Rate Using a Surrogate Convex Loss.
Proceedings of the 29th International Conference on Machine Learning, 2012

On the Hardness of Domain Adaptation and the Utility of Unlabeled Target Samples.
Proceedings of the Algorithmic Learning Theory - 23rd International Conference, 2012

Weighted Clustering.
Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2011
Multiclass Learnability and the ERM principle.
Proceedings of the COLT 2011, 2011

Discerning Linkage-Based Algorithms among Hierarchical Clustering Methods.
Proceedings of the IJCAI 2011, 2011

Access to Unlabeled Data can Speed up Prediction Time.
Proceedings of the 28th International Conference on Machine Learning, 2011

Learning a Classifier when the Labeling Is Known.
Proceedings of the Algorithmic Learning Theory - 22nd International Conference, 2011

2010
A theory of learning from different domains.
Machine Learning, 2010

Impossibility Theorems for Domain Adaptation.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Towards Property-Based Classification of Clustering Paradigms.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

ProbClean: A probabilistic duplicate detection system.
Proceedings of the 26th International Conference on Data Engineering, 2010

Characterization of Linkage-based Clustering.
Proceedings of the COLT 2010, 2010

2009
Modeling and Querying Possible Repairs in Duplicate Detection.
PVLDB, 2009

Learning Low Density Separators.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Clusterability: A Theoretical Study.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

A Uniqueness Theorem for Clustering.
Proceedings of the UAI 2009, 2009

Theory-Practice Interplay in Machine Learning - Emerging Theoretical Challenges.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

RTTS: towards enterprise-level real-time speech transcription and translation services.
Proceedings of the INTERSPEECH 2009, 2009

Agnostic Online Learning.
Proceedings of the COLT 2009, 2009

2008
A notion of task relatedness yielding provable multiple-task learning guarantees.
Machine Learning, 2008

Measures of Clustering Quality: A Working Set of Axioms for Clustering.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Does Unlabeled Data Provably Help? Worst-case Analysis of the Sample Complexity of Semi-Supervised Learning.
Proceedings of the 21st Annual Conference on Learning Theory, 2008

Relating Clustering Stability to Properties of Cluster Boundaries.
Proceedings of the 21st Annual Conference on Learning Theory, 2008

2007
Foreword.
Theor. Comput. Sci., 2007

A framework for statistical clustering with constant time approximation algorithms for K-median and K-means clustering.
Machine Learning, 2007

Stability of k -Means Clustering.
Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007

2006
Nonparametric change detection and estimation in large-scale sensor networks.
IEEE Trans. Signal Processing, 2006

Estimation of the number of operating sensors in large-scale sensor networks with mobile access.
IEEE Trans. Signal Processing, 2006

Alternative Measures of Computational Complexity with Applications to Agnostic Learning.
Proceedings of the Theory and Applications of Models of Computation, 2006

Analysis of Representations for Domain Adaptation.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Learning Bounds for Support Vector Machines with Learned Kernels.
Proceedings of the Learning Theory, 19th Annual Conference on Learning Theory, 2006

A Sober Look at Clustering Stability.
Proceedings of the Learning Theory, 19th Annual Conference on Learning Theory, 2006

2005
Nonparametric change detection in 2D random sensor field.
Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

2004
Detecting Change in Data Streams.
Proceedings of the (e)Proceedings of the Thirtieth International Conference on Very Large Data Bases, VLDB 2004, Toronto, Canada, August 31, 2004

A Framework for Statistical Clustering with a Constant Time Approximation Algorithms for K-Median Clustering.
Proceedings of the Learning Theory, 17th Annual Conference on Learning Theory, 2004

2003
Exploiting Task Relatedness for Mulitple Task Learning.
Proceedings of the Computational Learning Theory and Kernel Machines, 2003

2002
A theoretical framework for learning from a pool of disparate data sources.
Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2002

2001
Agnostic Boosting.
Proceedings of the Computational Learning Theory, 2001

Limitations of Learning via Embeddings in Euclidean Half-Spaces.
Proceedings of the Computational Learning Theory, 2001

2000
A Note on Non-complete Problems in NPImage.
J. Complexity, 2000

A Note On Vc-Dimension And Measure Of Sets Of Reals.
Combinatorics, Probability & Computing, 2000

A modal logic for subjective default reasoning.
Artif. Intell., 2000

Efficient Learning of Linear Perceptrons.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Localized Boosting.
Proceedings of the Thirteenth Annual Conference on Computational Learning Theory (COLT 2000), June 28, 2000

The Computational Complexity of Densest Region Detection.
Proceedings of the Thirteenth Annual Conference on Computational Learning Theory (COLT 2000), June 28, 2000

On the Difficulty of Approximately Maximizing Agreements.
Proceedings of the Thirteenth Annual Conference on Computational Learning Theory (COLT 2000), June 28, 2000

1999
VC-Dimension Analysis of Object Recognition Tasks.
Journal of Mathematical Imaging and Vision, 1999

Hardness Results for Neural Network Approximation Problems.
Proceedings of the Computational Learning Theory, 4th European Conference, 1999

1998
Self-Directed Learning and Its Relation to the VC-Dimension and to Teacher-Directed Learning.
Machine Learning, 1998

On the Existence of Propositional Proof Systems and Oracle-relativized Propositional Logic.
Electronic Colloquium on Computational Complexity (ECCC), 1998

Combinatorial Variability of Vapnik-chervonenkis Classes with Applications to Sample Compression Schemes.
Discrete Applied Mathematics, 1998

Can Finite Samples Detect Singularities of Reao-Valued Functions?
Algorithmica, 1998

1997
Learning Distributions by Their Density Levels: A Paradigm for Learning without a Teacher.
J. Comput. Syst. Sci., 1997

Scale-sensitive dimensions, uniform convergence, and learnability.
J. ACM, 1997

A Composition Theorem for Learning Algorithms with Applications to Geometric Concept Classes.
Proceedings of the Twenty-Ninth Annual ACM Symposium on the Theory of Computing, 1997

1996
A Composition Theorem for Learning Algorithms with Applications to Geometric Concept Classes
Electronic Colloquium on Computational Complexity (ECCC), 1996

Learning Changing Concepts by Exploiting the Structure of Change.
Proceedings of the Ninth Annual Conference on Computational Learning Theory, 1996

1995
A Parametrization Scheme for Classifying Models of PAC Learnability
Inf. Comput., July, 1995

Learning by Distances
Inf. Comput., March, 1995

Characterizations of Learnability for Classes of {0, ..., n}-Valued Functions.
J. Comput. Syst. Sci., 1995

Learning distributions by their density-levels - a paradigm for learning without a teacher.
Proceedings of the Computational Learning Theory, Second European Conference, 1995

Online learning versus offline learning.
Proceedings of the Computational Learning Theory, Second European Conference, 1995

A Note on VC-Dimension and Measures of Sets of Reals.
Proceedings of the Eigth Annual Conference on Computational Learning Theory, 1995

On Self-Directed Learning.
Proceedings of the Eigth Annual Conference on Computational Learning Theory, 1995

1994
On the Power of Randomization in On-Line Algorithms.
Algorithmica, 1994

A New Measure for the Study of On-Line Algorithms.
Algorithmica, 1994

a modal logic for subjective default reasoning
Proceedings of the Ninth Annual Symposium on Logic in Computer Science (LICS '94), 1994

Applying VC-dimension Analysis To Object Recognition.
Proceedings of the Computer Vision, 1994

On Ultrafilters and NP.
Proceedings of the Ninth Annual Structure in Complexity Theory Conference, Amsterdam, The Netherlands, June 28, 1994

Learnability with Restricted Focus of Attention guarantees Noise-Tolerance.
Proceedings of the Algorithmic Learning Theory, 1994

Applying VC-Dimension Analysis To 3D Object Recognition from Perspective Projections.
Proceedings of the 12th National Conference on Artificial Intelligence, Seattle, WA, USA, July 31, 1994

1993
Scale-sensitive Dimensions, Uniform Convergence, and Learnability
Proceedings of the 34th Annual Symposium on Foundations of Computer Science, 1993

Localization vs. Identification of Semi-Algebraic Sets.
Proceedings of the Sixth Annual ACM Conference on Computational Learning Theory, 1993

On Learning in the Limit and Non-Uniform (epsilon, delta)-Learning.
Proceedings of the Sixth Annual ACM Conference on Computational Learning Theory, 1993

Learning with Restricted Focus of Attention.
Proceedings of the Sixth Annual ACM Conference on Computational Learning Theory, 1993

1992
On the Theory of Average Case Complexity.
J. Comput. Syst. Sci., 1992

Can Finite Samples Detect Singularities of Real-Valued Functions?
Proceedings of the 24th Annual ACM Symposium on Theory of Computing, 1992

Characterizations of Learnability for Classes of {O, ..., n}-Valued Functions.
Proceedings of the Fifth Annual ACM Conference on Computational Learning Theory, 1992

1991
On the Limitation of the Global Time Assumption in Distributed Systems (Extended Abstract).
Proceedings of the Distributed Algorithms, 5th International Workshop, 1991

1990
On the Power of Randomization in Online Algorithms (Extended Abstract)
Proceedings of the 22nd Annual ACM Symposium on Theory of Computing, 1990

Learning by Distances.
Proceedings of the Third Annual Workshop on Computational Learning Theory, 1990

1989
On the Theory of Average Case Complexity
Proceedings of the 21st Annual ACM Symposium on Theory of Computing, 1989

A Parametrization Scheme for Classifying Models of Learnability.
Proceedings of the Second Annual Workshop on Computational Learning Theory, 1989

On the Theory of Average Case Complexity (abstract).
Proceedings of the Proceedings: Fourth Annual Structure in Complexity Theory Conference, 1989

1988
The Global Time Assumption and Semantics for Concurrent Systems.
Proceedings of the Seventh Annual ACM Symposium on Principles of Distributed Computing, 1988

1986
The Weak □* is Really Weaker than the Full □.
J. Symb. Log., 1986

Souslin trees and successors of singular cardinals.
Ann. Pure Appl. Logic, 1986


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