Sham M Kakade - Google Scholar Citations

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Citations	11903	8655
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Daniel HsuColumbia UniversityVerified email at cs.columbia.edu
Dean FosterAmazon, NYCVerified email at amazon.com
Anima AnandkumarCalifornia Institute of TechnologyVerified email at caltech.edu
Tong ZhangTencentVerified email at tongzhang-ml.org
John LangfordMicrosoft Research New YorkVerified email at hunch.net
Rong GeDuke UniversityVerified email at cs.duke.edu
Praneeth NetrapalliMicrosoft ResearchVerified email at microsoft.com
Nathaniel D. DawProfessor of Neurocience and Psychology, Princeton UniversityVerified email at princeton.edu
Aaron SidfordStanford UniversityVerified email at stanford.edu
Ambuj TewariAssociate Professor, Department of Statistics and Department of EECS, University of MichiganVerified email at umich.edu
Matthias SeegerProfessor of Computer Science, Ecole Polytechnique Federale de LausanneVerified email at epfl.ch
Chi JinPh.D student, UC BerkeleyVerified email at berkeley.edu
Michael KearnsProfessor of Computer Science, University of PennsylvaniaVerified email at cis.upenn.edu
Karthik SridharanCornell University, University of Pennsylvania, Toyota Technological InstituteVerified email at ttic.edu
Andreas KrauseProfessor of Computer Science, ETH ZurichVerified email at inf.ethz.ch
Yishay MansourTel Aviv UniversityVerified email at tau.ac.il
Prateek JainMicrosoft Research IndiaVerified email at microsoft.com
Shai Shalev-ShwartzThe Hebrew UniversityVerified email at cs.huji.ac.il
Eyal Even-DarVerified email at final.co.il
Kamalika ChaudhuriAssociate Professor of Computer Science, University of California, San DiegoVerified email at eng.ucsd.edu

Sham M Kakade

University of Washington

Verified email at cs.washington.edu - Homepage

Machine Learning Artificial Intelligence Statistics Optimization


Title	Cited by	Year
Cover trees for nearest neighbor A Beygelzimer, S Kakade, J Langford Proceedings of the 23rd international conference on Machine learning, 97-104, 2006	702	2006
Opponent interactions between serotonin and dopamine ND Daw, S Kakade, P Dayan Neural Networks 15 (4), 603-616, 2002	682	2002
Gaussian process optimization in the bandit setting: No regret and experimental design N Srinivas, A Krause, SM Kakade, M Seeger arXiv preprint arXiv:0912.3995, 2009	612	2009
Tensor decompositions for learning latent variable models A Anandkumar, R Ge, D Hsu, SM Kakade, M Telgarsky The Journal of Machine Learning Research 15 (1), 2773-2832, 2014	586	2014
A natural policy gradient S Kakade Advances in neural information processing systems 14, 1531-1538, 2001	462	2001
Multi-view clustering via canonical correlation analysis K Chaudhuri, SM Kakade, K Livescu, K Sridharan Proceedings of the 26th annual international conference on machine learning …, 2009	451	2009
A spectral algorithm for learning hidden markov models D Hsu, SM Kakade, T Zhang Journal of Computer and System Sciences, 2012	387	2012
Learning and selective attention P Dayan, S Kakade, PR Montague Nature neuroscience 3 (11s), 1218, 2000	380	2000
Dopamine: generalization and bonuses S Kakade, P Dayan Neural Networks 15 (4-6), 549-559, 2002	328	2002
Multi-label prediction via compressed sensing DJ Hsu, SM Kakade, J Langford, T Zhang Advances in neural information processing systems, 772-780, 2009	321	2009
Stochastic linear optimization under bandit feedback V Dani, TP Hayes, SM Kakade	305	2008
On the sample complexity of reinforcement learning SM Kakade University of London, 2003	305	2003
Learning mixtures of spherical gaussians: moment methods and spectral decompositions D Hsu, SM Kakade Proceedings of the 4th conference on Innovations in Theoretical Computer …, 2013	235	2013
A method of moments for mixture models and hidden Markov models A Anandkumar, D Hsu, SM Kakade Conference on Learning Theory, 33.1-33.34, 2012	230	2012
A spectral algorithm for latent dirichlet allocation A Anandkumar, DP Foster, DJ Hsu, SM Kakade, YK Liu Advances in Neural Information Processing Systems, 917-925, 2012	214	2012
Approximately optimal approximate reinforcement learning S Kakade, J Langford MACHINE LEARNING-INTERNATIONAL WORKSHOP THEN CONFERENCE-, 267-274, 2002	204	2002
Information-theoretic regret bounds for gaussian process optimization in the bandit setting N Srinivas, A Krause, SM Kakade, MW Seeger IEEE Transactions on Information Theory 58 (5), 3250-3265, 2012	201	2012
Robust matrix decomposition with sparse corruptions D Hsu, S Kakade, T Zhang Information Theory, IEEE Transactions on, 1-1, 2011	186	2011
On the complexity of linear prediction: Risk bounds, margin bounds, and regularization SM Kakade, K Sridharan, A Tewari Advances in neural information processing systems, 793-800, 2009	184	2009
A tensor approach to learning mixed membership community models A Anandkumar, R Ge, D Hsu, SM Kakade The Journal of Machine Learning Research 15 (1), 2239-2312, 2014	175	2014

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