Shai Ben-David

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Shai Shalev-ShwartzThe Hebrew UniversityVerified email at cs.huji.ac.il
Ruth UrnerAssociate Professor, York University, TorontoVerified email at eecs.yorku.ca
Maya (Margareta) AckermanWaveAI, Santa Clara UniversityVerified email at wave-ai.net
Dávid PálStaff Machine Learning Engineer, InstacartVerified email at instacart.com
Fernando PereiraVP, GoogleVerified email at google.com
Koby CrammerProfessor of Electrical Engineering, Technion - Israel Institute of TechnologyVerified email at ee.technion.ac.il
John BlitzerGoogle ResearchVerified email at google.com
John Shawe-TaylorUCLVerified email at cs.ucl.ac.uk
Hans Ulrich SimonRetired Professor, Dept. of Math., Ruhr-University BochumVerified email at rub.de
Michael LindenbaumProfessor of Computer Science, The TechnionVerified email at cs.technion.ac.il
Hassan AshtianiMcMaster UniversityVerified email at mcmaster.ca
Eyal KushilevitzComputer Science Department, TechnionVerified email at cs.technion.ac.il
Alex KuleszaResearch Scientist, GoogleVerified email at google.com
Jennifer Wortman VaughanSenior Principal Researcher, Microsoft Research, New York CityVerified email at microsoft.com
Nicolò Cesa-BianchiProfessor of Computer Science, Università degli Studi di Milano and Politecnico di MilanoVerified email at unimi.it
Ulrike von LuxburgUniversity of TübingenVerified email at informatik.uni-tuebingen.de
Allan BorodinProfessor of Computer Science, University of TorontoVerified email at cs.toronto.edu
Yishay MansourTel Aviv UniversityVerified email at tauex.tau.ac.il
Johannes GehrkeMicrosoftVerified email at microsoft.com
Shrinu KushagraGoogle DeepMindVerified email at deepmind.com

Shai Ben-David

Univerity of Waterloo, Canada

Verified email at uwaterloo.ca

Theoretical computer science Machine Learning Clustering Mathematical logic


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Understanding machine learning: From theory to algorithms S Shalev-Shwartz, S Ben-David Cambridge university press, 2014	8377	2014
A theory of learning from different domains S Ben-David, J Blitzer, K Crammer, A Kulesza, F Pereira, JW Vaughan Machine learning 79, 151-175, 2010	4002	2010
Analysis of representations for domain adaptation S Ben-David, J Blitzer, K Crammer, F Pereira Advances in neural information processing systems 19, 2006	2723	2006
Detecting change in data streams D Kifer, S Ben-David, J Gehrke VLDB 4, 180-191, 2004	1218	2004
Scale-sensitive dimensions, uniform convergence, and learnability N Alon, S Ben-David, N Cesa-Bianchi, D Haussler Journal of the ACM (JACM) 44 (4), 615-631, 1997	613	1997
On the power of randomization in on-line algorithms S Ben-David, A Borodin, R Karp, G Tardos, A Wigderson Algorithmica 11, 2-14, 1994	597	1994
Exploiting task relatedness for multiple task learning S Ben-David, R Schuller Learning Theory and Kernel Machines: 16th Annual Conference on Learning …, 2003	561	2003
Empirical risk minimization under fairness constraints M Donini, L Oneto, S Ben-David, JS Shawe-Taylor, M Pontil Advances in neural information processing systems 31, 2018	529	2018
Impossibility theorems for domain adaptation SB David, T Lu, T Luu, D Pál Proceedings of the Thirteenth International Conference on Artificial …, 2010	365	2010
On the theory of average case complexity S Ben-David, B Chor, O Goldreich Proceedings of the twenty-first annual ACM symposium on Theory of computing …, 1989	333	1989
A sober look at clustering stability S Ben-David, U Von Luxburg, D Pál Learning Theory: 19th Annual Conference on Learning Theory, COLT 2006 …, 2006	310	2006
Measures of clustering quality: A working set of axioms for clustering S Ben-David, M Ackerman Advances in neural information processing systems 21, 2008	268	2008
The temporal logic Sugar I Beer, S Ben-David, C Eisner, D Fisman, A Gringauze, Y Rodeh Computer Aided Verification: 13th International Conference, CAV 2001 Paris …, 2001	223	2001
On the difficulty of approximately maximizing agreements S Ben-David, N Eiron, PM Long Journal of Computer and System Sciences 66 (3), 496-514, 2003	216	2003
Agnostic Online Learning. S Ben-David, D Pál, S Shalev-Shwartz COLT 3, 1, 2009	207	2009
Characterizations of Learnability for Classes of {0,..., n)-Valued Functions S Ben-David, N Cesa-Bianchi, D Haussler, P Long	191*
Clusterability: A theoretical study M Ackerman, S Ben-David Artificial intelligence and statistics, 1-8, 2009	174	2009
A new measure for the study of on-line algorithms S Ben-David, A Borodin Algorithmica 11, 73-91, 1994	168	1994
Does Unlabeled Data Provably Help? Worst-case Analysis of the Sample Complexity of Semi-Supervised Learning. S Ben-David, T Lu, D Pál COLT, 33-44, 2008	166	2008
A uniqueness theorem for clustering RB Zadeh, S Ben-David arXiv preprint arXiv:1205.2600, 2012	145	2012

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