| Agnostically learning halfspaces AT Kalai, AR Klivans, Y Mansour, RA Servedio SIAM Journal on Computing 37 (6), 1777-1805, 2008 | 358 | 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 | 333 | 1999 |
| Learning DNF in time AR Klivans, R Servedio Proceedings of the thirty-third annual ACM symposium on Theory of computing …, 2001 | 257 | 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 | 252 | 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 | 228 | 2004 |
| Cryptographic hardness for learning intersections of halfspaces AR Klivans, AA Sherstov Journal of Computer and System Sciences 75 (1), 2-12, 2009 | 208 | 2009 |
| Efficient algorithms for outlier-robust regression A Klivans, PK Kothari, R Meka Conference On Learning Theory, 1420-1430, 2018 | 182 | 2018 |
| Hyperparameter optimization: A spectral approach E Hazan, A Klivans, Y Yuan arXiv preprint arXiv:1706.00764, 2017 | 168 | 2017 |
| Learning graphical models using multiplicative weights A Klivans, R Meka 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS …, 2017 | 144 | 2017 |
| Reliably learning the relu in polynomial time S Goel, V Kanade, A Klivans, J Thaler Conference on Learning Theory, 1004-1042, 2017 | 143 | 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 | 131 | 2008 |
| Learning Halfspaces with Malicious Noise. AR Klivans, PM Long, RA Servedio Journal of Machine Learning Research 10 (12), 2009 | 129 | 2009 |
| 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 | 117 | 2020 |
| Learning neural networks with two nonlinear layers in polynomial time S Goel, AR Klivans Conference on Learning Theory, 1470-1499, 2019 | 111* | 2019 |
| List-decodable linear regression S Karmalkar, A Klivans, P Kothari Advances in neural information processing systems 32, 2019 | 90 | 2019 |
| Learning one convolutional layer with overlapping patches S Goel, A Klivans, R Meka International conference on machine learning, 1783-1791, 2018 | 88 | 2018 |
| 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 | 84 | 2008 |
| 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 | 83 | 2011 |
| Toward Attribute Efficient Learning of Decision Lists and Parities. AR Klivans, RA Servedio, D Ron Journal of Machine Learning Research 7 (4), 2006 | 82 | 2006 |
| Superpolynomial lower bounds for learning one-layer neural networks using gradient descent S Goel, A Gollakota, Z Jin, S Karmalkar, A Klivans International Conference on Machine Learning, 3587-3596, 2020 | 79 | 2020 |
