Tensor decompositions for learning latent variable models A Anandkumar, R Ge, D Hsu, SM Kakade, M Telgarsky Journal of Machine Learning Research 15, 2773-2832, 2014 | 914 | 2014 |

Escaping from saddle points—online stochastic gradient for tensor decomposition R Ge, F Huang, C Jin, Y Yuan Conference on Learning Theory, 797-842, 2015 | 777 | 2015 |

Matrix completion has no spurious local minimum R Ge, JD Lee, T Ma Advances in Neural Information Processing Systems 29, 2973-2981, 2016 | 471 | 2016 |

How to escape saddle points efficiently C Jin, R Ge, P Netrapalli, SM Kakade, MI Jordan arXiv preprint arXiv:1703.00887, 2017 | 464 | 2017 |

Generalization and equilibrium in generative adversarial nets (gans) S Arora, R Ge, Y Liang, T Ma, Y Zhang arXiv preprint arXiv:1703.00573, 2017 | 412 | 2017 |

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 | 406 | 2012 |

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 | 396 | 2013 |

Computing a nonnegative matrix factorization---Provably S Arora, R Ge, R Kannan, A Moitra SIAM Journal on Computing 45 (4), 1582-1611, 2016 | 388 | 2016 |

Provable bounds for learning some deep representations S Arora, A Bhaskara, R Ge, T Ma International Conference on Machine Learning, 584-592, 2014 | 336 | 2014 |

Stronger generalization bounds for deep nets via a compression approach S Arora, R Ge, B Neyshabur, Y Zhang arXiv preprint arXiv:1802.05296, 2018 | 280 | 2018 |

No spurious local minima in nonconvex low rank problems: A unified geometric analysis R Ge, C Jin, Y Zheng arXiv preprint arXiv:1704.00708, 2017 | 272 | 2017 |

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 | 243 | 2014 |

New algorithms for learning in presence of errors S Arora, R Ge Automata, Languages and Programming, 403-415, 2011 | 239 | 2011 |

Global convergence of policy gradient methods for the linear quadratic regulator M Fazel, R Ge, SM Kakade, M Mesbahi arXiv preprint arXiv:1801.05039, 2018 | 208* | 2018 |

New algorithms for learning incoherent and overcomplete dictionaries S Arora, R Ge, A Moitra Conference on Learning Theory, 779-806, 2014 | 198 | 2014 |

Computational complexity and information asymmetry in financial products S Arora, B Barak, M Brunnermeier, R Ge ICS, 49-65, 2010 | 181 | 2010 |

Simple, efficient, and neural algorithms for sparse coding S Arora, R Ge, T Ma, A Moitra Proceedings of Machine Learning Research, 2015 | 176 | 2015 |

Learning one-hidden-layer neural networks with landscape design R Ge, JD Lee, T Ma arXiv preprint arXiv:1711.00501, 2017 | 163 | 2017 |

Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization R Frostig, R Ge, S Kakade, A Sidford International Conference on Machine Learning, 2540-2548, 2015 | 129 | 2015 |

Efficient approaches for escaping higher order saddle points in non-convex optimization A Anandkumar, R Ge Conference on learning theory, 81-102, 2016 | 123 | 2016 |