Understanding deep learning (still) requires rethinking generalization C Zhang, S Bengio, M Hardt, B Recht, O Vinyals Communications of the ACM 64 (3), 107-115, 2021 | 7362 | 2021 |

Exact matrix completion via convex optimization E Candes, B Recht Communications of the ACM 55 (6), 111-119, 2012 | 7263 | 2012 |

Random features for large-scale kernel machines A Rahimi, B Recht Advances in neural information processing systems 20, 2007 | 4893 | 2007 |

Guaranteed minimum-rank solutions of linear matrix equations via nuclear norm minimization B Recht, M Fazel, PA Parrilo SIAM Review 52 (3), 471-501, 2010 | 4210 | 2010 |

Hogwild!: A lock-free approach to parallelizing stochastic gradient descent F Niu, B Recht, C Ré, SJ Wright Advances in Neural Information Processing Systems 24, 693--701, 2011 | 2788* | 2011 |

Physical one-way functions R Pappu, B Recht, J Taylor, N Gershenfeld Science 297 (5589), 2026, 2002 | 2533 | 2002 |

Do imagenet classifiers generalize to imagenet? B Recht, R Roelofs, L Schmidt, V Shankar International conference on machine learning, 5389-5400, 2019 | 2109* | 2019 |

The Convex Geometry of Linear Inverse Problems V Chandrasekaran, B Recht, PA Parrilo, AS Willsky Foundations of Computational Mathematics 12 (6), 805-849, 2012 | 1477 | 2012 |

Train faster, generalize better: Stability of stochastic gradient descent M Hardt, B Recht, Y Singer International conference on machine learning, 1225-1234, 2016 | 1405 | 2016 |

The marginal value of adaptive gradient methods in machine learning AC Wilson, R Roelofs, M Stern, N Srebro, B Recht Advances in neural information processing systems 30, 2017 | 1308 | 2017 |

Compressed sensing off the grid G Tang, BN Bhaskar, P Shah, B Recht IEEE Transactions on Information Theory 59 (11), 7465-7490, 2013 | 1270 | 2013 |

A simpler approach to matrix completion B Recht The Journal of Machine Learning Research 12, 3413-3430, 2011 | 1194 | 2011 |

Plenoxels: Radiance fields without neural networks S Fridovich-Keil, A Yu, M Tancik, Q Chen, B Recht, A Kanazawa Proceedings of the IEEE/CVF conference on computer vision and pattern ¡K, 2022 | 1077 | 2022 |

Tensor completion and low-n-rank tensor recovery via convex optimization S Gandy, B Recht, I Yamada Inverse problems 27 (2), 025010, 2011 | 901 | 2011 |

Gradient descent only converges to minimizers JD Lee, M Simchowitz, MI Jordan, B Recht Conference on learning theory, 1246-1257, 2016 | 896* | 2016 |

Weighted sums of random kitchen sinks: Replacing minimization with randomization in learning A Rahimi, B Recht Advances in Neural Information Processing Systems 21, 2008 | 874 | 2008 |

A tour of reinforcement learning: The view from continuous control B Recht Annual Review of Control, Robotics, and Autonomous Systems 2 (1), 253-279, 2019 | 745 | 2019 |

Analysis and design of optimization algorithms via integral quadratic constraints L Lessard, B Recht, A Packard SIAM Journal on Optimization 26 (1), 57-95, 2016 | 678 | 2016 |

Simple random search of static linear policies is competitive for reinforcement learning H Mania, A Guy, B Recht Advances in neural information processing systems 31, 2018 | 677* | 2018 |

Atomic norm denoising with applications to line spectral estimation BN Bhaskar, G Tang, B Recht IEEE Transactions on Signal Processing 61 (23), 5987-5999, 2013 | 654 | 2013 |