Anima Anandkumar
Anima Anandkumar
Verified email at caltech.edu
TitleCited byYear
Tensor decompositions for learning latent variable models
A Anandkumar, R Ge, D Hsu, SM Kakade, M Telgarsky
arXiv preprint arXiv:1210.7559 64, 70-72, 0
596*
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
2302012
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
2142012
Distributed algorithms for learning and cognitive medium access with logarithmic regret
A Anandkumar, N Michael, AK Tang, A Swami
IEEE Journal on Selected Areas in Communications 29 (4), 731-745, 2011
1882011
Learning latent tree graphical models
MJ Choi, VYF Tan, A Anandkumar, AS Willsky
Journal of Machine Learning Research 12 (May), 1771-1812, 2011
1842011
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
1752014
Learning sparsely used overcomplete dictionaries
A Agarwal, A Anandkumar, P Jain, P Netrapalli, R Tandon
Conference on Learning Theory, 123-137, 2014
1672014
Opportunistic spectrum access with multiple users: Learning under competition
A Anandkumar, N Michael, A Tang
INFOCOM, 2010 Proceedings IEEE, 1-9, 2010
1582010
Non-convex robust PCA
P Netrapalli, UN Niranjan, S Sanghavi, A Anandkumar, P Jain
Advances in Neural Information Processing Systems, 1107-1115, 2014
1532014
Beating the perils of non-convexity: Guaranteed training of neural networks using tensor methods
M Janzamin, H Sedghi, A Anandkumar
arXiv preprint arXiv:1506.08473, 2015
123*2015
High-dimensional structure estimation in Ising models: Local separation criterion
A Anandkumar, VYF Tan, F Huang, AS Willsky
The Annals of Statistics 40 (3), 1346-1375, 2012
96*2012
Guaranteed Non-Orthogonal Tensor Decomposition via Alternating Rank- Updates
A Anandkumar, R Ge, M Janzamin
arXiv preprint arXiv:1402.5180, 2014
772014
Two SVDs Su ffice: Spectral decompositions for probabilistic topic modeling and latent Dirichlet allocation
YK Liu, A Anandkumar, DP Foster, D Hsu, SM Kakade
Neural Information Processing Systems (NIPS), 2012
742012
Online tensor methods for learning latent variable models
F Huang, UN Niranjan, MU Hakeem, A Anandkumar
The Journal of Machine Learning Research 16 (1), 2797-2835, 2015
66*2015
High-dimensional Gaussian graphical model selection: Walk summability and local separation criterion
A Anandkumar, VYF Tan, F Huang, AS Willsky
Journal of Machine Learning Research 13 (Aug), 2293-2337, 2012
60*2012
A large-deviation analysis of the maximum-likelihood learning of Markov tree structures
VYF Tan, A Anandkumar, L Tong, AS Willsky
IEEE Transactions on Information Theory 57 (3), 1714-1735, 2011
572011
Efficient approaches for escaping higher order saddle points in non-convex optimization
A Anandkumar, R Ge
Conference on Learning Theory, 81-102, 2016
562016
Learning topic models and latent Bayesian networks under expansion constraints
A Anandkumar, D Hsu, A Javanmard, SM Kakade
arXiv preprint arXiv:1209.5350, 2012
54*2012
Detection of Gauss–Markov random fields with nearest-neighbor dependency
A Anandkumar, L Tong, A Swami
IEEE Transactions on Information Theory 55 (2), 816-827, 2009
512009
Type-based random access for distributed detection over multiaccess fading channels
A Anandkumar, L Tong
IEEE Transactions on Signal Processing 55 (10), 5032-5043, 2007
502007
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Articles 1–20