Sham M Kakade
Title
Cited by
Cited by
Year
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
12042009
Tensor decompositions for learning latent variable models
A Anandkumar, R Ge, D Hsu, SM Kakade, M Telgarsky
Journal of Machine Learning Research 15, 2773-2832, 2014
8902014
Cover trees for nearest neighbor
A Beygelzimer, S Kakade, J Langford
Proceedings of the 23rd international conference on Machine learning, 97-104, 2006
8622006
Opponent interactions between serotonin and dopamine
ND Daw, S Kakade, P Dayan
Neural networks 15 (4-6), 603-616, 2002
8042002
A natural policy gradient
S Kakade
Advances in neural information processing systems 14, 1531-1538, 2001
7712001
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
6582009
Stochastic linear optimization under bandit feedback
V Dani, TP Hayes, SM Kakade
5202008
A spectral algorithm for learning hidden markov models
D Hsu, SM Kakade, T Zhang
Journal of Computer and System Sciences, 2012
4902012
On the sample complexity of reinforcement learning
SM Kakade
University of London, 2003
4822003
Approximately optimal approximate reinforcement learning
S Kakade, J Langford
MACHINE LEARNING-INTERNATIONAL WORKSHOP THEN CONFERENCE-, 267-274, 2002
4722002
Learning and selective attention
P Dayan, S Kakade, PR Montague
Nature neuroscience 3 (11), 1218-1223, 2000
4582000
Multi-label prediction via compressed sensing
DJ Hsu, SM Kakade, J Langford, T Zhang
Advances in neural information processing systems, 772-780, 2009
4432009
How to escape saddle points efficiently
C Jin, R Ge, P Netrapalli, SM Kakade, MI Jordan
arXiv preprint arXiv:1703.00887, 2017
4312017
Dopamine: generalization and bonuses
S Kakade, P Dayan
Neural Networks 15 (4-6), 549-559, 2002
4262002
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
4062012
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
4062011
Learning a predictable and generative vector representation for objects
R Girdhar, DF Fouhey, M Rodriguez, A Gupta
European Conference on Computer Vision, 484-499, 2016
4042016
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
2952012
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
2922013
A tail inequality for quadratic forms of subgaussian random vectors
D Hsu, S Kakade, T Zhang
Electronic Communications in Probability 17, 2012
2852012
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Articles 1–20