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
Ulrike von LuxburgUniversity of TübingenVerified email at informatik.uni-tuebingen.de
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
Yishay MansourTel Aviv UniversityVerified email at tauex.tau.ac.il
Nicolò Cesa-BianchiProfessor of Computer Science, Università degli Studi di Milano and Politecnico di MilanoVerified email at unimi.it
Allan BorodinProfessor of Computer Science, University of TorontoVerified email at cs.toronto.edu
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	6938	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	3348	2010
Analysis of representations for domain adaptation S Ben-David, J Blitzer, K Crammer, F Pereira Advances in neural information processing systems 19, 2006	2285	2006
Detecting change in data streams D Kifer, S Ben-David, J Gehrke VLDB 4, 180-191, 2004	1148	2004
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	578	1994
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	574	1997
Exploiting task relatedness for multiple task learning S Ben-David, R Schuller Learning Theory and Kernel Machines: 16th Annual Conference on Learning …, 2003	530	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	437	2018
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	323	1989
Impossibility theorems for domain adaptation SB David, T Lu, T Luu, D Pál Proceedings of the Thirteenth International Conference on Artificial …, 2010	315	2010
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	300	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	250	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	219	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	208	2003
Characterizations of Learnability for Classes of {0,..., n)-Valued Functions S Ben-David, N Cesa-Bianchi, D Haussler, P Long	174*
Clusterability: A theoretical study M Ackerman, S Ben-David Artificial intelligence and statistics, 1-8, 2009	171	2009
Agnostic Online Learning. S Ben-David, D Pál, S Shalev-Shwartz COLT 3, 1, 2009	164	2009
A new measure for the study of on-line algorithms S Ben-David, A Borodin Algorithmica 11, 73-91, 1994	162	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	159	2008
A uniqueness theorem for clustering RB Zadeh, S Ben-David arXiv preprint arXiv:1205.2600, 2012	140	2012

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