Introduction to derivative-free optimization AR Conn, K Scheinberg, LN Vicente Society for Industrial and Applied Mathematics, 2009 | 1527 | 2009 |

Efficient SVM training using low-rank kernel representations S Fine, K Scheinberg Journal of Machine Learning Research 2 (Dec), 243-264, 2001 | 735 | 2001 |

Optimization for machine learning S Sra, S Nowozin, SJ Wright Mit Press, 2012 | 487 | 2012 |

Recent progress in unconstrained nonlinear optimization without derivatives AR Conn, K Scheinberg, PL Toint Mathematical programming 79 (1-3), 397, 1997 | 323 | 1997 |

Fast alternating linearization methods for minimizing the sum of two convex functions D Goldfarb, S Ma, K Scheinberg Mathematical Programming 141 (1-2), 349-382, 2013 | 260 | 2013 |

On the convergence of derivative-free methods for unconstrained optimization AR Conn, K Scheinberg, PL Toint Approximation theory and optimization: tributes to MJD Powell, 83-108, 1997 | 230 | 1997 |

Global convergence of general derivative-free trust-region algorithms to first-and second-order critical points AR Conn, K Scheinberg, LN Vicente SIAM Journal on Optimization 20 (1), 387-415, 2009 | 211 | 2009 |

Sparse inverse covariance selection via alternating linearization methods K Scheinberg, S Ma, D Goldfarb Advances in neural information processing systems, 2101-2109, 2010 | 189 | 2010 |

SARAH: A novel method for machine learning problems using stochastic recursive gradient LM Nguyen, J Liu, K Scheinberg, M Takáč arXiv preprint arXiv:1703.00102, 2017 | 186 | 2017 |

Efficient block-coordinate descent algorithms for the group lasso Z Qin, K Scheinberg, D Goldfarb Mathematical Programming Computation 5 (2), 143-169, 2013 | 171 | 2013 |

IBM Research TRECVID-2006 Video Retrieval System. M Campbell, A Haubold, S Ebadollahi, D Joshi, MR Naphade, A Natsev, ... TRECVID, 175-182, 2006 | 154 | 2006 |

A derivative free optimization algorithm in practice A Conn, K Scheinberg, P Toint 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and …, 1998 | 151 | 1998 |

Geometry of interpolation sets in derivative free optimization AR Conn, K Scheinberg, LN Vicente Mathematical programming 111 (1-2), 141-172, 2008 | 135 | 2008 |

An efficient implementation of an active set method for SVMs K Scheinberg Journal of Machine Learning Research 7 (Oct), 2237-2257, 2006 | 108 | 2006 |

Interior point trajectories in semidefinite programming D Goldfarb, K Scheinberg SIAM Journal on Optimization 8 (4), 871-886, 1998 | 108 | 1998 |

A derivative-free algorithm for least-squares minimization H Zhang, AR Conn, K Scheinberg SIAM Journal on Optimization 20 (6), 3555-3576, 2010 | 83 | 2010 |

Self-correcting geometry in model-based algorithms for derivative-free unconstrained optimization K Scheinberg, PL Toint SIAM Journal on Optimization 20 (6), 3512-3532, 2010 | 80 | 2010 |

Geometry of sample sets in derivative-free optimization: polynomial regression and underdetermined interpolation AR Conn, K Scheinberg, LN Vicente IMA journal of numerical analysis 28 (4), 721-748, 2008 | 78 | 2008 |

SGD and Hogwild! convergence without the bounded gradients assumption LM Nguyen, PH Nguyen, M van Dijk, P Richtárik, K Scheinberg, M Takáč arXiv preprint arXiv:1802.03801, 2018 | 69 | 2018 |

Duality and optimality conditions A Shapiro, K Scheinberg Handbook of semidefinite programming, 67-110, 2000 | 69 | 2000 |