Shai BenDavid
According to our database^{1},
Shai BenDavid
authored at least 116 papers
between 1986 and 2019.
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Bibliography
2019
A SemiSupervised Framework of Clustering Selection for DeDuplication.
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
Semisupervised clustering for deduplication.
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
Multitask {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 ThirtySecond AAAI Conference on Artificial Intelligence, 2018
SampleEfficient Learning of Mixtures.
Proceedings of the ThirtySecond AAAI Conference on Artificial Intelligence, 2018
2016
A Characterization of LinkageBased Hierarchical Clustering.
J. Mach. Learn. Res., 2016
Foundations of Unsupervised Learning (Dagstuhl Seminar 16382).
Dagstuhl Reports, 2016
Clustering with SameCluster 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 ThirtyFirst Conference on Uncertainty in Artificial Intelligence, 2015
Hierarchical Label Queries with DataDependent Partitions.
Proceedings of The 28th Conference on Learning Theory, 2015
Multitask 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 adaptationcan 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 BiClustering.
Proceedings of the 30th International Conference on Machine Learning, 2013
PLAL: Clusterbased 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 AdaptationCan 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 TwentySixth AAAI Conference on Artificial Intelligence, 2012
2011
Multiclass Learnability and the ERM principle.
Proceedings of the COLT 2011, 2011
Discerning LinkageBased 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 PropertyBased 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 69 December 2010, 2010
ProbClean: A probabilistic duplicate detection system.
Proceedings of the 26th International Conference on Data Engineering, 2010
Characterization of Linkagebased 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
TheoryPractice Interplay in Machine Learning  Emerging Theoretical Challenges.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009
RTTS: towards enterpriselevel realtime 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 multipletask 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? Worstcase Analysis of the Sample Complexity of SemiSupervised 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 Kmedian and Kmeans 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 largescale sensor networks.
IEEE Trans. Signal Processing, 2006
Estimation of the number of operating sensors in largescale 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 KMedian 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 HalfSpaces.
Proceedings of the Computational Learning Theory, 2001
2000
A Note on Noncomplete Problems in NPImage.
J. Complexity, 2000
A Note On VcDimension 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
VCDimension 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
SelfDirected Learning and Its Relation to the VCDimension and to TeacherDirected Learning.
Machine Learning, 1998
On the Existence of Propositional Proof Systems and Oraclerelativized Propositional Logic.
Electronic Colloquium on Computational Complexity (ECCC), 1998
Combinatorial Variability of Vapnikchervonenkis Classes with Applications to Sample Compression Schemes.
Discrete Applied Mathematics, 1998
Can Finite Samples Detect Singularities of ReaoValued Functions?
Algorithmica, 1998
1997
Learning Distributions by Their Density Levels: A Paradigm for Learning without a Teacher.
J. Comput. Syst. Sci., 1997
Scalesensitive dimensions, uniform convergence, and learnability.
J. ACM, 1997
A Composition Theorem for Learning Algorithms with Applications to Geometric Concept Classes.
Proceedings of the TwentyNinth 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 densitylevels  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 VCDimension and Measures of Sets of Reals.
Proceedings of the Eigth Annual Conference on Computational Learning Theory, 1995
On SelfDirected Learning.
Proceedings of the Eigth Annual Conference on Computational Learning Theory, 1995
1994
On the Power of Randomization in OnLine Algorithms.
Algorithmica, 1994
A New Measure for the Study of OnLine 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 VCdimension 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 NoiseTolerance.
Proceedings of the Algorithmic Learning Theory, 1994
Applying VCDimension Analysis To 3D Object Recognition from Perspective Projections.
Proceedings of the 12th National Conference on Artificial Intelligence, Seattle, WA, USA, July 31, 1994
1993
Scalesensitive Dimensions, Uniform Convergence, and Learnability
Proceedings of the 34th Annual Symposium on Foundations of Computer Science, 1993
Localization vs. Identification of SemiAlgebraic Sets.
Proceedings of the Sixth Annual ACM Conference on Computational Learning Theory, 1993
On Learning in the Limit and NonUniform (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 RealValued 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