Koby Crammer

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Coauteurs

Fernando PereiraVP and Engineering Fellow, GoogleAdresse e-mail validée de google.com
Mark DredzeJohns Hopkins UniversityAdresse e-mail validée de cs.jhu.edu
Alex KuleszaResearch Scientist, GoogleAdresse e-mail validée de google.com
Jennifer Wortman VaughanSenior Principal Researcher, Microsoft Research, New York CityAdresse e-mail validée de microsoft.com
Partha TalukdarGoogle Research and IISc BangaloreAdresse e-mail validée de iisc.ac.in
Ryan McDonaldResearch Scientist, GoogleAdresse e-mail validée de google.com
Shai Shalev-ShwartzThe Hebrew UniversityAdresse e-mail validée de cs.huji.ac.il
Shai Ben-DavidUniverity of Waterloo, CanadaAdresse e-mail validée de uwaterloo.ca
Joseph (Yossi) KeshetProfessor, Dept. of Computer Science, Bar-Ilan UniversityAdresse e-mail validée de cs.biu.ac.il
Ofer DekelMicrosoft ResearchAdresse e-mail validée de microsoft.com
Shie MannorProfessor of Electrical Engineering @ Technion & Researcher @ Nvidia ResearchAdresse e-mail validée de technion.ac.il
Michael KearnsProfessor of Computer Science, University of PennsylvaniaAdresse e-mail validée de cis.upenn.edu
Slobodan VuceticProfessor of Computer Science, Temple UniversityAdresse e-mail validée de temple.edu
Hadas BenistyYaleAdresse e-mail validée de yale.edu
David MalahProfessor Emeritus, Electrical Engineering, Technion - I.I.TAdresse e-mail validée de ee.technion.ac.il
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyAdresse e-mail validée de cs.berkeley.edu
Yevgeny SeldinProfessor, Department of Computer Science, University of CopenhagenAdresse e-mail validée de di.ku.dk
Kuzman GanchevGoogle IncAdresse e-mail validée de google.com
Ran El-YanivProfessor of Computer Science, Technion - Israel Institute of TechnologyAdresse e-mail validée de cs.technion.ac.il
Axel BernalData Scientist, Human Longevity IncAdresse e-mail validée de humanlongevity.com

Koby Crammer

Professor of Electrical Engineering, Technion - Israel Institute of Technology

Adresse e-mail validée de ee.technion.ac.il

Machine Learning Big Data


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
On the algorithmic implementation of multiclass kernel-based vector machines K Crammer, Y Singer Journal of machine learning research 2 (Dec), 265-292, 2001	2553	2001
Online passive-aggressive algorithms K Crammer, O Dekel, J Keshet, S Shalev-Shwartz, Y Singer Journal of Machine Learning Research 7 (Mar), 551-585, 2006	2034	2006
A theory of learning from different domains S Ben-David, J Blitzer, K Crammer, A Kulesza, F Pereira, JW Vaughan Machine learning 79 (1-2), 151-175, 2010	1441	2010
Analysis of representations for domain adaptation S Ben-David, J Blitzer, K Crammer, F Pereira Advances in neural information processing systems, 137-144, 2007	1160	2007
Online large-margin training of dependency parsers R McDonald, K Crammer, F Pereira Proceedings of the 43rd annual meeting on association for computational …, 2005	948	2005
On the learnability and design of output codes for multiclass problems K Crammer, Y Singer Machine learning 47 (2-3), 201-233, 2002	909	2002
Pranking with ranking K Crammer, Y Singer Advances in neural information processing systems, 641-647, 2002	775	2002
Ultraconservative online algorithms for multiclass problems K Crammer, Y Singer Journal of Machine Learning Research 3 (Jan), 951-991, 2003	704	2003
Confidence-weighted linear classification M Dredze, K Crammer, F Pereira Proceedings of the 25th international conference on Machine learning, 264-271, 2008	500	2008
Learning bounds for domain adaptation J Blitzer, K Crammer, A Kulesza, F Pereira, J Wortman Advances in neural information processing systems, 129-136, 2008	372	2008
Adaptive regularization of weight vectors K Crammer, A Kulesza, M Dredze Advances in neural information processing systems, 414-422, 2009	315	2009
Margin analysis of the LVQ algorithm K Crammer, R Gilad-Bachrach, A Navot, N Tishby Advances in neural information processing systems, 479-486, 2003	271	2003
New regularized algorithms for transductive learning PP Talukdar, K Crammer Joint European Conference on Machine Learning and Knowledge Discovery in …, 2009	251	2009
A family of additive online algorithms for category ranking K Crammer, Y Singer Journal of Machine Learning Research 3 (Feb), 1025-1058, 2003	245	2003
Learning from multiple sources K Crammer, M Kearns, J Wortman Journal of Machine Learning Research 9 (Aug), 1757-1774, 2008	216	2008
Online classification on a budget K Crammer, J Kandola, Y Singer Advances in neural information processing systems, 225-232, 2004	190	2004
Breaking the curse of kernelization: Budgeted stochastic gradient descent for large-scale svm training Z Wang, K Crammer, S Vucetic Journal of Machine Learning Research 13 (Oct), 3103-3131, 2012	182	2012
Kernel design using boosting K Crammer, J Keshet, Y Singer Advances in neural information processing systems, 553-560, 2003	178	2003
Robust support vector machine training via convex outlier ablation L Xu, K Crammer, D Schuurmans AAAI 6, 536-542, 2006	176	2006
Exact convex confidence-weighted learning K Crammer, M Dredze, F Pereira Advances in Neural Information Processing Systems, 345-352, 2009	168	2009

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