フォロー
Sham M Kakade
Sham M Kakade
Harvard University
確認したメール アドレス: seas.harvard.edu - ホームページ
タイトル
引用先
引用先
年
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
28962009
A natural policy gradient
S Kakade
Advances in neural information processing systems 14, 1531-1538, 2001
16522001
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
13812014
Approximately optimal approximate reinforcement learning
S Kakade, J Langford
MACHINE LEARNING-INTERNATIONAL WORKSHOP THEN CONFERENCE-, 267-274, 2002
13212002
Cover trees for nearest neighbor
A Beygelzimer, S Kakade, J Langford
Proceedings of the 23rd international conference on Machine learning, 97-104, 2006
11762006
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
10792012
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
10792011
Opponent interactions between serotonin and dopamine
ND Daw, S Kakade, P Dayan
Neural networks 15 (4-6), 603-616, 2002
10402002
How to escape saddle points efficiently
C Jin, R Ge, P Netrapalli, SM Kakade, MI Jordan
International conference on machine learning, 1724-1732, 2017
10312017
Stochastic Linear Optimization under Bandit Feedback.
V Dani, TP Hayes, SM Kakade
COLT 2, 3, 2008
9712008
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
9702009
Meta-learning with implicit gradients
A Rajeswaran, C Finn, SM Kakade, S Levine
Advances in neural information processing systems 32, 2019
9682019
On the sample complexity of reinforcement learning
SM Kakade
PQDT-Global, 2003
8712003
Robust aggregation for federated learning
K Pillutla, SM Kakade, Z Harchaoui
IEEE Transactions on Signal Processing 70, 1142-1154, 2022
7362022
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
7202018
A spectral algorithm for learning hidden markov models
D Hsu, SM Kakade, T Zhang
Journal of Computer and System Sciences, 2012
6292012
Learning and selective attention
P Dayan, S Kakade, PR Montague
Nature neuroscience 3 (11), 1218-1223, 2000
6232000
Dopamine: generalization and bonuses
S Kakade, P Dayan
Neural Networks 15 (4-6), 549-559, 2002
5802002
Online meta-learning
C Finn, A Rajeswaran, S Kakade, S Levine
International conference on machine learning, 1920-1930, 2019
5452019
Multi-label prediction via compressed sensing
DJ Hsu, SM Kakade, J Langford, T Zhang
Advances in neural information processing systems 22, 2009
5332009
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