Learning topic models--going beyond SVD S Arora, R Ge, A Moitra 2012 IEEE 53rd annual symposium on foundations of computer science, 1-10, 2012 | 414 | 2012 |
Computing a nonnegative matrix factorization---Provably S Arora, R Ge, R Kannan, A Moitra SIAM Journal on Computing 45 (4), 1582-1611, 2016 | 405 | 2016 |
A practical algorithm for topic modeling with provable guarantees S Arora, R Ge, Y Halpern, D Mimno, A Moitra, D Sontag, Y Wu, M Zhu International Conference on Machine Learning, 280-288, 2013 | 398 | 2013 |
Settling the polynomial learnability of mixtures of gaussians A Moitra, G Valiant 2010 IEEE 51st Annual Symposium on Foundations of Computer Science, 93-102, 2010 | 293 | 2010 |
Robust estimators in high-dimensions without the computational intractability I Diakonikolas, G Kamath, D Kane, J Li, A Moitra, A Stewart SIAM Journal on Computing 48 (2), 742-864, 2019 | 244 | 2019 |
New algorithms for learning incoherent and overcomplete dictionaries S Arora, R Ge, A Moitra Conference on Learning Theory, 779-806, 2014 | 199 | 2014 |
Efficiently learning mixtures of two Gaussians AT Kalai, A Moitra, G Valiant Proceedings of the forty-second ACM symposium on Theory of computing, 553-562, 2010 | 192 | 2010 |
Simple, efficient, and neural algorithms for sparse coding S Arora, R Ge, T Ma, A Moitra Conference on learning theory, 113-149, 2015 | 179 | 2015 |
A nearly tight sum-of-squares lower bound for the planted clique problem B Barak, S Hopkins, J Kelner, PK Kothari, A Moitra, A Potechin SIAM Journal on Computing 48 (2), 687-735, 2019 | 134 | 2019 |
Some results on greedy embeddings in metric spaces T Leighton, A Moitra Discrete & Computational Geometry 44 (3), 686-705, 2010 | 126 | 2010 |
Being robust (in high dimensions) can be practical I Diakonikolas, G Kamath, DM Kane, J Li, A Moitra, A Stewart International Conference on Machine Learning, 999-1008, 2017 | 124 | 2017 |
Smoothed analysis of tensor decompositions A Bhaskara, M Charikar, A Moitra, A Vijayaraghavan Proceedings of the forty-sixth annual ACM symposium on Theory of computing …, 2014 | 115 | 2014 |
Noisy tensor completion via the sum-of-squares hierarchy B Barak, A Moitra Conference on Learning Theory, 417-445, 2016 | 105 | 2016 |
Algorithms and hardness for robust subspace recovery M Hardt, A Moitra Conference on Learning Theory, 354-375, 2013 | 96 | 2013 |
An information complexity approach to extended formulations M Braverman, A Moitra Proceedings of the forty-fifth annual ACM symposium on Theory of computing …, 2013 | 88 | 2013 |
Super-resolution, extremal functions and the condition number of Vandermonde matrices A Moitra Proceedings of the forty-seventh annual ACM symposium on Theory of computing …, 2015 | 87 | 2015 |
Robustly learning a gaussian: Getting optimal error, efficiently I Diakonikolas, G Kamath, DM Kane, J Li, A Moitra, A Stewart Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete …, 2018 | 86 | 2018 |
Efficient and explicit coding for interactive communication R Gelles, A Moitra, A Sahai 2011 IEEE 52nd Annual Symposium on Foundations of Computer Science, 768-777, 2011 | 76 | 2011 |
An almost optimal algorithm for computing nonnegative rank A Moitra SIAM Journal on Computing 45 (1), 156-173, 2016 | 75* | 2016 |
Provable ICA with unknown Gaussian noise, and implications for Gaussian mixtures and autoencoders S Arora, R Ge, A Moitra, S Sachdeva arXiv preprint arXiv:1206.5349, 2012 | 73 | 2012 |