Anima Anandkumar
Anima Anandkumar
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Cited by
Cited by
SegFormer: Simple and efficient design for semantic segmentation with transformers
E Xie, W Wang, Z Yu, A Anandkumar, JM Alvarez, P Luo
Advances in Neural Information Processing Systems 34, 12077-12090, 2021
Tensor decompositions for learning latent variable models
A Anandkumar, R Ge, D Hsu, S Kakade, M Telgarsky
The Journal of Machine Learning Research 15 (1), 2773-2832, 2014
Born again neural networks
T Furlanello, Z Lipton, M Tschannen, L Itti, A Anandkumar
International Conference on Machine Learning, 1607-1616, 2018
Fourier Neural Operator for Parametric Partial Differential Equations
Z Li, NB Kovachki, K Azizzadenesheli, B Lui, K Bhattacharya, A Stuart, ...
International Conference on Learning Representations, 2021
signSGD: Compressed optimisation for non-convex problems
J Bernstein, YX Wang, K Azizzadenesheli, A Anandkumar
International Conference on Machine Learning, 560-569, 2018
Stochastic activation pruning for robust adversarial defense
GS Dhillon, K Azizzadenesheli, ZC Lipton, J Bernstein, J Kossaifi, ...
arXiv preprint arXiv:1803.01442, 2018
Deep active learning for named entity recognition
Y Shen, H Yun, ZC Lipton, Y Kronrod, A Anandkumar
arXiv preprint arXiv:1707.05928, 2017
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
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
Tensorly: Tensor learning in python
J Kossaifi, Y Panagakis, A Anandkumar, M Pantic
arXiv preprint arXiv:1610.09555, 2016
A spectral algorithm for latent dirichlet allocation
A Anandkumar, DP Foster, DJ Hsu, SM Kakade, YK Liu
Advances in neural information processing systems 25, 2012
Non-convex robust PCA
P Netrapalli, N UN, S Sanghavi, A Anandkumar, P Jain
Advances in neural information processing systems 27, 2014
Neural operator: Graph kernel network for partial differential equations
Z Li, N Kovachki, K Azizzadenesheli, B Liu, K Bhattacharya, A Stuart, ...
arXiv preprint arXiv:2003.03485, 2020
A tensor spectral approach to learning mixed membership community models
A Anandkumar, R Ge, D Hsu, S Kakade
Conference on Learning Theory, 867-881, 2013
Learning latent tree graphical models
MJ Choi, VYF Tan, A Anandkumar, AS Willsky
Journal of Machine Learning Research 12, 1771-1812, 2011
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
Neural lander: Stable drone landing control using learned dynamics
G Shi, X Shi, M O’Connell, R Yu, K Azizzadenesheli, A Anandkumar, ...
2019 International Conference on Robotics and Automation (ICRA), 9784-9790, 2019
Opportunistic spectrum access with multiple users: Learning under competition
A Anandkumar, N Michael, A Tang
2010 Proceedings IEEE INFOCOM, 1-9, 2010
Neural Operator: Learning Maps Between Function Spaces With Applications to PDEs
N Kovachki, Z Li, B Liu, K Azizzadenesheli, K Bhattacharya, A Stuart, ...
Journal of Machine Learning Research 24 (89), 1-97, 2023
Long-term forecasting using tensor-train rnns
R Yu, S Zheng, A Anandkumar, Y Yue
Arxiv, 2017
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