Koby Crammer

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Fernando PereiraVP and Engineering Fellow, GoogleEmail verificata su google.com
Mark DredzeJohns Hopkins UniversityEmail verificata su cs.jhu.edu
Alex KuleszaResearch Scientist, GoogleEmail verificata su google.com
Jennifer Wortman VaughanSenior Principal Researcher, Microsoft Research, New York CityEmail verificata su microsoft.com
Partha TalukdarGoogle Research and IISc BangaloreEmail verificata su iisc.ac.in
Ryan McDonaldResearch Scientist, GoogleEmail verificata su google.com
Shai Shalev-ShwartzThe Hebrew UniversityEmail verificata su cs.huji.ac.il
Shai Ben-DavidUniverity of Waterloo, CanadaEmail verificata su uwaterloo.ca
Joseph (Yossi) KeshetProfessor, Dept. of Computer Science, Bar-Ilan UniversityEmail verificata su cs.biu.ac.il
Ofer DekelMicrosoft ResearchEmail verificata su microsoft.com
Shie MannorProfessor of Electrical Engineering @ Technion & Researcher @ Nvidia ResearchEmail verificata su technion.ac.il
Michael KearnsProfessor of Computer Science, University of PennsylvaniaEmail verificata su cis.upenn.edu
Slobodan VuceticProfessor of Computer Science, Temple UniversityEmail verificata su temple.edu
Hadas BenistyYaleEmail verificata su yale.edu
David MalahProfessor Emeritus, Electrical Engineering, Technion - I.I.TEmail verificata su ee.technion.ac.il
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyEmail verificata su cs.berkeley.edu
Yevgeny SeldinProfessor, Department of Computer Science, University of CopenhagenEmail verificata su di.ku.dk
Kuzman GanchevGoogle IncEmail verificata su google.com
Ran El-YanivProfessor of Computer Science, Technion - Israel Institute of TechnologyEmail verificata su cs.technion.ac.il
Axel BernalData Scientist, Human Longevity IncEmail verificata su humanlongevity.com

Koby Crammer

Professor of Electrical Engineering, Technion - Israel Institute of Technology

Email verificata su ee.technion.ac.il

Machine Learning Big Data


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
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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