| A concise second-order complexity analysis for unconstrained optimization using high-order regularized models | 1 | 0.35 | 2020 |
| Universal Regularization Methods: Varying the Power, the Smoothness and the Accuracy. | 0 | 0.34 | 2019 |
| QPLIB: a library of quadratic programming instances | 3 | 0.38 | 2019 |
| Second-Order Optimality and Beyond: Characterization and Evaluation Complexity in Convexly Constrained Nonlinear Optimization. | 4 | 0.41 | 2018 |
| SHARP WORST-CASE EVALUATION COMPLEXITY BOUNDS FOR ARBITRARY-ORDER NONCONVEX OPTIMIZATION WITH INEXPENSIVE CONSTRAINTS | 2 | 0.38 | 2018 |
| SHARP WORST-CASE EVALUATION COMPLEXITY BOUNDS FOR ARBITRARY-ORDER NONCONVEX OPTIMIZATION WITH INEXPENSIVE CONSTRAINTS | 2 | 0.38 | 2018 |
| Optimality of orders one to three and beyond: characterization and evaluation complexity in constrained nonconvex optimization. | 1 | 0.36 | 2017 |
| Corrigendum: On the complexity of finding first-order critical points in constrained nonlinear optimization | 1 | 0.35 | 2017 |
| A dual gradient-projection method for large-scale strictly convex quadratic problems. | 2 | 0.37 | 2017 |
| Evaluation complexity bounds for smooth constrained nonlinear optimisation using scaled KKT conditions, high-order models and the criticality measure $χ$. | 1 | 0.35 | 2017 |
| Improved second-order evaluation complexity for unconstrained nonlinear optimization using high-order regularized models. | 3 | 0.42 | 2017 |
| The State-of-the-Art of Preconditioners for Sparse Linear Least-Squares Problems. | 6 | 0.47 | 2017 |
| Worst-case evaluation complexity of regularization methods for smooth unconstrained optimization using Hölder continuous gradients | 0 | 0.34 | 2017 |
| A dimer-type saddle search algorithm with preconditioning and linesearch. | 1 | 0.43 | 2016 |
| Adaptive augmented Lagrangian methods: algorithms and practical numerical experience | 2 | 0.36 | 2016 |
| A Note on Performance Profiles for Benchmarking Software. | 5 | 0.42 | 2016 |
| On the Evaluation Complexity of Constrained Nonlinear Least-Squares and General Constrained Nonlinear Optimization Using Second-Order Methods | 5 | 0.49 | 2015 |
| A Nonmonotone Filter SQP Method: Local Convergence and Numerical Results | 4 | 0.40 | 2015 |
| CUTEst: a Constrained and Unconstrained Testing Environment with safe threads for mathematical optimization | 56 | 1.70 | 2015 |
| A note on “On fast trust region methods for quadratic models with linear constraints”, by Michael J.D. Powell | 0 | 0.34 | 2015 |
| Projected Krylov Methods for Saddle-Point Systems. | 6 | 0.55 | 2014 |
| A Filter Method with Unified Step Computation for Nonlinear Optimization. | 8 | 0.47 | 2014 |
| On the complexity of finding first-order critical points in constrained nonlinear optimization. | 9 | 0.61 | 2014 |
| Trajectory-following methods for large-scale degenerate convex quadratic programming. | 5 | 0.43 | 2013 |
| On the Evaluation Complexity of Cubic Regularization Methods for Potentially Rank-Deficient Nonlinear Least-Squares Problems and Its Relevance to Constrained Nonlinear Optimization. | 8 | 0.63 | 2013 |
| Updating the regularization parameter in the adaptive cubic regularization algorithm | 11 | 0.65 | 2012 |
| On the Oracle Complexity of First-Order and Derivative-Free Algorithms for Smooth Nonconvex Minimization | 16 | 1.09 | 2012 |
| Evaluation complexity of adaptive cubic regularization methods for convex unconstrained optimization. | 7 | 0.61 | 2012 |
| How good are extrapolated bi-projection methods for linear feasibility problems? | 1 | 0.36 | 2012 |
| Adaptive cubic regularisation methods for unconstrained optimization. Part II: worst-case function- and derivative-evaluation complexity | 64 | 3.04 | 2011 |
| On the Evaluation Complexity of Composite Function Minimization with Applications to Nonconvex Nonlinear Programming | 12 | 0.74 | 2011 |
| A Second Derivative SQP Method: Local Convergence and Practical Issues | 19 | 0.79 | 2010 |
| On solving trust-region and other regularised subproblems in optimization1 | 0 | 0.34 | 2010 |
| Preconditioning Saddle-Point Systems with Applications in Optimization | 11 | 0.70 | 2010 |
| A Second Derivative SQP Method: Global Convergence | 24 | 1.06 | 2010 |
| Spectral Analysis of Saddle Point Matrices with Indefinite Leading Blocks | 15 | 0.78 | 2009 |
| How good are projection methods for convex feasibility problems? | 6 | 0.63 | 2008 |
| Using constraint preconditioners with regularized saddle-point problems | 11 | 0.64 | 2007 |
| A numerical evaluation of sparse direct solvers for the solution of large sparse symmetric linear systems of equations | 65 | 4.20 | 2007 |
| FILTRANE, a Fortran 95 filter-trust-region package for solving nonlinear least-squares and nonlinear feasibility problems | 6 | 0.57 | 2007 |
| Implicit-Factorization Preconditioning and Iterative Solvers for Regularized Saddle-Point Systems | 23 | 1.58 | 2006 |
| Sensitivity of trust-region algorithms to their parameters | 11 | 1.23 | 2005 |
| A Filter-Trust-Region Method for Unconstrained Optimization | 40 | 2.17 | 2005 |
| An evaluation of sparse direct symmetric solvers: an introduction and preliminary findings | 0 | 0.34 | 2004 |
| A Multidimensional Filter Algorithm for Nonlinear Equations and Nonlinear Least-Squares | 33 | 1.34 | 2004 |
| An algorithm for nonlinear optimization using linear programming and equality constrained subproblems | 30 | 1.38 | 2004 |
| GALAHAD, a library of thread-safe Fortran 90 packages for large-scale nonlinear optimization | 73 | 5.37 | 2003 |
| CUTEr and SifDec: A constrained and unconstrained testing environment, revisited | 227 | 16.37 | 2003 |
| Global Convergence of a Trust-Region SQP-Filter Algorithm for General Nonlinear Programming | 109 | 13.17 | 2002 |
| Componentwise fast convergence in the solution of full-rank systems of nonlinear equations | 6 | 0.90 | 2002 |
