Sham M Kakade

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Daniel HsuColumbia UniversityVerified email at cs.columbia.edu
Dean FosterAmazon, NYCVerified email at amazon.com
Praneeth NetrapalliGoogle ResearchVerified email at google.com
Rong GeDuke UniversityVerified email at cs.duke.edu
Anima AnandkumarCalifornia Institute of Technology and NVIDIAVerified email at caltech.edu
Tong ZhangUIUCVerified email at tongzhang-ml.org
Prateek JainGoogle Research IndiaVerified email at google.com
John LangfordMicrosoft Research New YorkVerified email at hunch.net
Chi JinAssistant Professor, Princeton UniversityVerified email at princeton.edu
Alekh AgarwalGoogleVerified email at google.com
Jason D. LeeAssociate Professor of Electrical Engineering and Computer Science, Princeton UniversityVerified email at princeton.edu
Aaron SidfordStanford UniversityVerified email at stanford.edu
Peter DayanMPI for Biological CyberneticsVerified email at tue.mpg.de
Matthias SeegerPrincipal Applied Scientist, Amazon, BerlinVerified email at amazon.de
Ambuj Tewari | अम्बुज तिवारीProfessor, Statistics and EECS, University of MichiganVerified email at umich.edu
Andreas KrauseProfessor of Computer Science, ETH ZurichVerified email at inf.ethz.ch
Akshay KrishnamurthyUniversity of Massachusetts AmherstVerified email at cs.umass.edu
Aravind RajeswaranMeta AI, UC BerkeleyVerified email at cs.washington.edu
Cyril ZhangMicrosoft Research NYCVerified email at microsoft.com
Ali FarhadiProfessor, Computer Science and Engineering, University of WashingtonVerified email at cs.uw.edu

Sham M Kakade

Harvard University

Verified email at seas.harvard.edu - Homepage

Machine Learning Artificial Intelligence Statistics Optimization


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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	2961	2009
A natural policy gradient S Kakade Advances in neural information processing systems 14, 1531-1538, 2001	1676	2001
Tensor decompositions for learning latent variable models. A Anandkumar, R Ge, DJ Hsu, SM Kakade, M Telgarsky J. Mach. Learn. Res. 15 (1), 2773-2832, 2014	1398	2014
Approximately optimal approximate reinforcement learning S Kakade, J Langford MACHINE LEARNING-INTERNATIONAL WORKSHOP THEN CONFERENCE-, 267-274, 2002	1370	2002
Cover trees for nearest neighbor A Beygelzimer, S Kakade, J Langford Proceedings of the 23rd international conference on Machine learning, 97-104, 2006	1192	2006
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	1111	2012
Information-Theoretic Regret Boundsfor Gaussian Process Optimization in the Bandit Setting N Srinivas, A Krause, S Kakade, M Seeger Information Theory, IEEE Transactions on, 1-1, 2011	1111	2011
How to escape saddle points efficiently C Jin, R Ge, P Netrapalli, SM Kakade, MI Jordan International conference on machine learning, 1724-1732, 2017	1052	2017
Opponent interactions between serotonin and dopamine ND Daw, S Kakade, P Dayan Neural networks 15 (4-6), 603-616, 2002	1051	2002
Meta-learning with implicit gradients A Rajeswaran, C Finn, SM Kakade, S Levine Advances in neural information processing systems 32, 2019	990	2019
Stochastic linear optimization under bandit feedback V Dani, TP Hayes, SM Kakade 21st Annual Conference on Learning Theory, 355-366, 2008	989	2008
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	972	2009
On the sample complexity of reinforcement learning SM Kakade PQDT-Global, 2003	898	2003
Robust aggregation for federated learning K Pillutla, SM Kakade, Z Harchaoui IEEE Transactions on Signal Processing 70, 1142-1154, 2022	765	2022
Global convergence of policy gradient methods for the linear quadratic regulator M Fazel, R Ge, S Kakade, M Mesbahi International conference on machine learning, 1467-1476, 2018	740	2018
A spectral algorithm for learning hidden markov models D Hsu, SM Kakade, T Zhang Journal of Computer and System Sciences, 2012	633	2012
Learning and selective attention P Dayan, S Kakade, PR Montague Nature neuroscience 3 (11), 1218-1223, 2000	625	2000
Dopamine: generalization and bonuses S Kakade, P Dayan Neural Networks 15 (4-6), 549-559, 2002	588	2002
Online meta-learning C Finn, A Rajeswaran, S Kakade, S Levine International conference on machine learning, 1920-1930, 2019	559	2019
Multi-label prediction via compressed sensing DJ Hsu, SM Kakade, J Langford, T Zhang Advances in neural information processing systems 22, 2009	534	2009

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