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 | 559 | 2013 |

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 | 549 | 2012 |

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 | 526 | 2019 |

Computing a nonnegative matrix factorization--provably S Arora, R Ge, R Kannan, A Moitra Proceedings of the forty-fourth annual ACM symposium on Theory of computing …, 2012 | 511 | 2012 |

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 | 400 | 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 | 270 | 2017 |

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 | 269 | 2019 |

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 | 267 | 2010 |

New algorithms for learning incoherent and overcomplete dictionaries S Arora, R Ge, A Moitra Conference on Learning Theory, 779-806, 2014 | 231 | 2014 |

Simple, efficient, and neural algorithms for sparse coding S Arora, R Ge, T Ma, A Moitra Conference on learning theory, 113-149, 2015 | 228 | 2015 |

Noisy tensor completion via the sum-of-squares hierarchy B Barak, A Moitra Conference on Learning Theory, 417-445, 2016 | 185 | 2016 |

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 | 172 | 2015 |

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 | 170 | 2014 |

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 | 147 | 2018 |

Some results on greedy embeddings in metric spaces T Leighton, A Moitra Discrete & Computational Geometry 44, 686-705, 2010 | 137 | 2010 |

Algorithms and hardness for robust subspace recovery M Hardt, A Moitra Conference on Learning Theory, 354-375, 2013 | 136 | 2013 |

Optimality and sub-optimality of PCA I: Spiked random matrix models A Perry, AS Wein, AS Bandeira, A Moitra The Annals of Statistics 46 (5), 2416-2451, 2018 | 117 | 2018 |

Algorithmic aspects of machine learning A Moitra Cambridge University Press, 2018 | 113 | 2018 |

An information complexity approach to extended formulations M Braverman, A Moitra Proceedings of the forty-fifth annual ACM symposium on Theory of computing …, 2013 | 104 | 2013 |

Provable ICA with unknown Gaussian noise, with implications for Gaussian mixtures and autoencoders S Arora, R Ge, A Moitra, S Sachdeva Advances in Neural Information Processing Systems 25, 2012 | 102 | 2012 |