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 | 296 | 2010 |

Estimating the unseen: an n/log (n)-sample estimator for entropy and support size, shown optimal via new CLTs G Valiant, P Valiant Proceedings of the forty-third annual ACM symposium on Theory of computing …, 2011 | 273 | 2011 |

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 | 195 | 2010 |

Learning from untrusted data M Charikar, J Steinhardt, G Valiant Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing …, 2017 | 176 | 2017 |

Optimal algorithms for testing closeness of discrete distributions SO Chan, I Diakonikolas, P Valiant, G Valiant Proceedings of the twenty-fifth annual ACM-SIAM symposium on Discrete …, 2014 | 152 | 2014 |

An automatic inequality prover and instance optimal identity testing G Valiant, P Valiant SIAM Journal on Computing 46 (1), 429-455, 2017 | 147 | 2017 |

Learning polynomials with neural networks A Andoni, R Panigrahy, G Valiant, L Zhang International conference on machine learning, 1908-1916, 2014 | 142 | 2014 |

The power of linear estimators G Valiant, P Valiant 2011 IEEE 52nd Annual Symposium on Foundations of Computer Science, 403-412, 2011 | 140 | 2011 |

Estimating the Unseen: Improved Estimators for Entropy and other Properties. P Valiant, G Valiant NIPS, 2157-2165, 2013 | 105 | 2013 |

Braess's paradox in large random graphs G Valiant, T Roughgarden Random Structures & Algorithms 37 (4), 495-515, 2010 | 87 | 2010 |

Designing network protocols for good equilibria HL Chen, T Roughgarden, G Valiant SIAM Journal on Computing 39 (5), 1799-1832, 2010 | 86 | 2010 |

Designing network protocols for good equilibria HL Chen, T Roughgarden, G Valiant SIAM Journal on Computing 39 (5), 1799-1832, 2010 | 86 | 2010 |

Finding correlations in subquadratic time, with applications to learning parities and juntas G Valiant 2012 IEEE 53rd Annual Symposium on Foundations of Computer Science, 11-20, 2012 | 83 | 2012 |

Resilience: A criterion for learning in the presence of arbitrary outliers J Steinhardt, M Charikar, G Valiant arXiv preprint arXiv:1703.04940, 2017 | 82 | 2017 |

Testing *k*-Modal Distributions: Optimal Algorithms via ReductionsC Daskalakis, I Diakonikolas, RA Servedio, G Valiant, P Valiant Proceedings of the twenty-fourth annual ACM-SIAM symposium on Discrete …, 2013 | 79 | 2013 |

A CLT and tight lower bounds for estimating entropy. G Valiant, P Valiant Electronic Colloquium on Computational Complexity (ECCC) 17 (179), 9, 2010 | 79 | 2010 |

Martian subsurface properties and crater formation processes inferred from fresh impact crater geometries ST Stewart, GJ Valiant Meteoritics & Planetary Science 41 (10), 1509-1537, 2006 | 76 | 2006 |

Finding correlations in subquadratic time, with applications to learning parities and the closest pair problem G Valiant Journal of the ACM (JACM) 62 (2), 1-45, 2015 | 75 | 2015 |

Disentangling gaussians AT Kalai, A Moitra, G Valiant Communications of the ACM 55 (2), 113-120, 2012 | 65 | 2012 |

Memory, communication, and statistical queries J Steinhardt, G Valiant, S Wager Conference on Learning Theory, 1490-1516, 2016 | 60 | 2016 |