Adaptive cubic regularisation methods for unconstrained optimization. Part I: motivation, convergence and numerical results C Cartis, NIM Gould, PL Toint Mathematical Programming 127 (2), 245-295, 2011 | 243 | 2011 |

Adaptive cubic regularisation methods for unconstrained optimization. Part II: worst-case function-and derivative-evaluation complexity C Cartis, NIM Gould, PL Toint Mathematical programming 130 (2), 295-319, 2011 | 196 | 2011 |

On the complexity of steepest descent, Newton's and regularized Newton's methods for nonconvex unconstrained optimization problems C Cartis, NIM Gould, PL Toint Siam journal on optimization 20 (6), 2833-2852, 2010 | 175 | 2010 |

Compressed sensing: How sharp is the restricted isometry property JD Blanchard, C Cartis, J Tanner Arxiv preprint arXiv:1004.5026, 2010 | 170* | 2010 |

Global rates of convergence for nonconvex optimization on manifolds N Boumal, PA Absil, C Cartis IMA Journal of Numerical Analysis 39 (1), 1-33, 2018 | 99 | 2018 |

On the evaluation complexity of composite function minimization with applications to nonconvex nonlinear programming C Cartis, NIM Gould, PL Toint SIAM Journal on Optimization 21 (4), 1721-1739, 2011 | 73 | 2011 |

Complexity bounds for second-order optimality in unconstrained optimization C Cartis, NIM Gould, PL Toint Journal of Complexity 28 (1), 93-108, 2012 | 67 | 2012 |

Phase transitions for greedy sparse approximation algorithms JD Blanchard, C Cartis, J Tanner, A Thompson Applied and Computational Harmonic Analysis 30 (2), 188-203, 2011 | 66 | 2011 |

An adaptive cubic regularization algorithm for nonconvex optimization with convex constraints and its function-evaluation complexity C Cartis, NIM Gould, PL Toint IMA Journal of Numerical Analysis 32 (4), 1662-1695, 2012 | 61 | 2012 |

On the oracle complexity of first-order and derivative-free algorithms for smooth nonconvex minimization C Cartis, NIM Gould, PL Toint SIAM Journal on Optimization 22 (1), 66-86, 2012 | 48 | 2012 |

Global convergence rate analysis of unconstrained optimization methods based on probabilistic models C Cartis, K Scheinberg Mathematical Programming 169 (2), 337-375, 2018 | 47 | 2018 |

On the complexity of finding first-order critical points in constrained nonlinear optimization C Cartis, NIM Gould, PL Toint Mathematical Programming 144 (1-2), 93-106, 2014 | 42 | 2014 |

Convergence of a regularized Euclidean residual algorithm for nonlinear least-squares S Bellavia, C Cartis, NIM Gould, B Morini, PL Toint SIAM Journal on Numerical Analysis 48 (1), 1-29, 2010 | 41 | 2010 |

Trust-region and other regularisations of linear least-squares problems C Cartis, NIM Gould, PL Toint BIT Numerical Mathematics 49 (1), 21-53, 2009 | 41 | 2009 |

On the evaluation complexity of cubic regularization methods for potentially rank-deficient nonlinear least-squares problems and its relevance to constrained nonlinear optimization C Cartis, NIM Gould, PL Toint SIAM Journal on Optimization 23 (3), 1553-1574, 2013 | 40 | 2013 |

Evaluation complexity of adaptive cubic regularization methods for convex unconstrained optimization C Cartis, NIM Gould, PL Toint Optimization Methods and Software 27 (2), 197-219, 2012 | 31 | 2012 |

Can top-of-atmosphere radiation measurements constrain climate predictions? Part I: Tuning SFB Tett, MJ Mineter, C Cartis, DJ Rowlands, P Liu Journal of Climate 26 (23), 9348-9366, 2013 | 30* | 2013 |

Some disadvantages of a Mehrotra-type primal-dual corrector interior point algorithm for linear programming C Cartis Applied Numerical Mathematics 59 (5), 1110-1119, 2009 | 30 | 2009 |

Decay properties of restricted isometry constants JD Blanchard, C Cartis, J Tanner IEEE Signal Processing Letters 16 (7), 572-575, 2009 | 28 | 2009 |

A new and improved quantitative recovery analysis for iterative hard thresholding algorithms in compressed sensing C Cartis, A Thompson IEEE Transactions on Information Theory 61 (4), 2019-2042, 2015 | 27 | 2015 |