Agnostically learning halfspaces AT Kalai, AR Klivans, Y Mansour, RA Servedio SIAM Journal on Computing 37 (6), 1777-1805, 2008 | 325 | 2008 |

Graph nonisomorphism has subexponential size proofs unless the polynomial-time hierarchy collapses AR Klivans, D Van Melkebeek Proceedings of the Thirty-First Annual ACM Symposium on Theory of Computing …, 1999 | 311 | 1999 |

Learning DNF in time AR Klivans, R Servedio Proceedings of the thirty-third annual ACM symposium on Theory of computing …, 2001 | 246 | 2001 |

Randomness efficient identity testing of multivariate polynomials AR Klivans, D Spielman Proceedings of the thirty-third annual ACM symposium on Theory of computing …, 2001 | 244 | 2001 |

Learning intersections and thresholds of halfspaces AR Klivans, R O'Donnell, RA Servedio Journal of Computer and System Sciences 68 (4), 808-840, 2004 | 213 | 2004 |

Cryptographic hardness for learning intersections of halfspaces AR Klivans, AA Sherstov Journal of Computer and System Sciences 75 (1), 2-12, 2009 | 192 | 2009 |

Efficient algorithms for outlier-robust regression A Klivans, PK Kothari, R Meka Conference On Learning Theory, 1420-1430, 2018 | 151 | 2018 |

Hyperparameter optimization: A spectral approach E Hazan, A Klivans, Y Yuan arXiv preprint arXiv:1706.00764, 2017 | 139 | 2017 |

Reliably learning the relu in polynomial time S Goel, V Kanade, A Klivans, J Thaler Conference on Learning Theory, 1004-1042, 2017 | 129 | 2017 |

Learning Halfspaces with Malicious Noise. AR Klivans, PM Long, RA Servedio Journal of Machine Learning Research 10 (12), 2009 | 118 | 2009 |

Learning graphical models using multiplicative weights A Klivans, R Meka 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS …, 2017 | 113 | 2017 |

Learning geometric concepts via Gaussian surface area AR Klivans, R O'Donnell, RA Servedio 2008 49th Annual IEEE Symposium on Foundations of Computer Science, 541-550, 2008 | 108 | 2008 |

Learning neural networks with two nonlinear layers in polynomial time S Goel, AR Klivans Conference on Learning Theory, 1470-1499, 2019 | 95* | 2019 |

Good subnetworks provably exist: Pruning via greedy forward selection M Ye, C Gong, L Nie, D Zhou, A Klivans, Q Liu International Conference on Machine Learning, 10820-10830, 2020 | 87 | 2020 |

An FPTAS for# knapsack and related counting problems P Gopalan, A Klivans, R Meka, D Štefankovic, S Vempala, E Vigoda 2011 IEEE 52nd Annual Symposium on Foundations of Computer Science, 817-826, 2011 | 80 | 2011 |

List-decoding Reed-Muller codes over small fields P Gopalan, AR Klivans, D Zuckerman Proceedings of the fortieth annual ACM symposium on Theory of computing, 265-274, 2008 | 80 | 2008 |

Learning one convolutional layer with overlapping patches S Goel, A Klivans, R Meka International Conference on Machine Learning, 1783-1791, 2018 | 78 | 2018 |

Toward Attribute Efficient Learning of Decision Lists and Parities. AR Klivans, RA Servedio, D Ron Journal of Machine Learning Research 7 (4), 2006 | 75 | 2006 |

Learnability beyond AC^{0}JC Jackson, AR Klivans, RA Servedio Proceedings of the thiry-fourth annual ACM symposium on Theory of computing …, 2002 | 74 | 2002 |

Agnostically learning decision trees P Gopalan, AT Kalai, AR Klivans Proceedings of the fortieth annual ACM symposium on Theory of computing, 527-536, 2008 | 71 | 2008 |