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
Tong ZhangUIUCVerified email at tongzhang-ml.org
Anima AnandkumarCalifornia Institute of Technology and NVIDIAVerified email at caltech.edu
John LangfordMicrosoft Research New YorkVerified email at hunch.net
Prateek JainGoogle Research IndiaVerified email at google.com
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
Matthias SeegerPrincipal Applied Scientist, Amazon, BerlinVerified email at amazon.de
Ambuj Tewari | अम्बुज तिवारीProfessor, Statistics and EECS, University of MichiganVerified email at umich.edu
Akshay KrishnamurthyUniversity of Massachusetts AmherstVerified email at cs.umass.edu
Andreas KrauseProfessor of Computer Science, ETH ZurichVerified email at inf.ethz.ch
Aravind RajeswaranMeta AI, UC BerkeleyVerified email at cs.washington.edu
Simon Shaolei DuAssistant Professor, School of Computer Science and Engineering, University of WashingtonVerified email at cs.washington.edu
Lin F. Yang (杨林)Assistant Professor, Department of Electrical and Computer Engineering @ UCLAVerified email at ee.ucla.edu
Yishay MansourTel Aviv UniversityVerified email at tauex.tau.ac.il

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	2896	2009
A natural policy gradient S Kakade Advances in neural information processing systems 14, 1531-1538, 2001	1652	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	1381	2014
Approximately optimal approximate reinforcement learning S Kakade, J Langford MACHINE LEARNING-INTERNATIONAL WORKSHOP THEN CONFERENCE-, 267-274, 2002	1321	2002
Cover trees for nearest neighbor A Beygelzimer, S Kakade, J Langford Proceedings of the 23rd international conference on Machine learning, 97-104, 2006	1176	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	1079	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	1079	2011
Opponent interactions between serotonin and dopamine ND Daw, S Kakade, P Dayan Neural networks 15 (4-6), 603-616, 2002	1040	2002
How to escape saddle points efficiently C Jin, R Ge, P Netrapalli, SM Kakade, MI Jordan International conference on machine learning, 1724-1732, 2017	1031	2017
Stochastic Linear Optimization under Bandit Feedback. V Dani, TP Hayes, SM Kakade COLT 2, 3, 2008	971	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	970	2009
Meta-learning with implicit gradients A Rajeswaran, C Finn, SM Kakade, S Levine Advances in neural information processing systems 32, 2019	968	2019
On the sample complexity of reinforcement learning SM Kakade PQDT-Global, 2003	871	2003
Robust aggregation for federated learning K Pillutla, SM Kakade, Z Harchaoui IEEE Transactions on Signal Processing 70, 1142-1154, 2022	736	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	720	2018
A spectral algorithm for learning hidden markov models D Hsu, SM Kakade, T Zhang Journal of Computer and System Sciences, 2012	629	2012
Learning and selective attention P Dayan, S Kakade, PR Montague Nature neuroscience 3 (11), 1218-1223, 2000	623	2000
Dopamine: generalization and bonuses S Kakade, P Dayan Neural Networks 15 (4-6), 549-559, 2002	580	2002
Online meta-learning C Finn, A Rajeswaran, S Kakade, S Levine International conference on machine learning, 1920-1930, 2019	545	2019
Multi-label prediction via compressed sensing DJ Hsu, SM Kakade, J Langford, T Zhang Advances in neural information processing systems 22, 2009	533	2009

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