| 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 | 423 | 2012 |
| Computing a nonnegative matrix factorization---Provably S Arora, R Ge, R Kannan, A Moitra SIAM Journal on Computing 45 (4), 1582-1611, 2016 | 418 | 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 | 412 | 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 | 302 | 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 | 256 | 2019 |
| New algorithms for learning incoherent and overcomplete dictionaries S Arora, R Ge, A Moitra Conference on Learning Theory, 779-806, 2014 | 202 | 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 | 201 | 2010 |
| Simple, efficient, and neural algorithms for sparse coding S Arora, R Ge, T Ma, A Moitra Conference on learning theory, 113-149, 2015 | 187 | 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 | 140 | 2019 |
| 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 | 135 | 2017 |
| Some results on greedy embeddings in metric spaces T Leighton, A Moitra Discrete & Computational Geometry 44 (3), 686-705, 2010 | 126 | 2010 |
| 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 | 118 | 2014 |
| Noisy tensor completion via the sum-of-squares hierarchy B Barak, A Moitra Conference on Learning Theory, 417-445, 2016 | 109 | 2016 |
| Algorithms and hardness for robust subspace recovery M Hardt, A Moitra Conference on Learning Theory, 354-375, 2013 | 99 | 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 | 97 | 2015 |
| An information complexity approach to extended formulations M Braverman, A Moitra Proceedings of the forty-fifth annual ACM symposium on Theory of computing …, 2013 | 90 | 2013 |
| 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 | 89 | 2018 |
| An almost optimal algorithm for computing nonnegative rank A Moitra SIAM Journal on Computing 45 (1), 156-173, 2016 | 76* | 2016 |
| 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 |
| 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 | 74 | 2012 |
