DOI10.1137/120869687zbMath1277.68092OpenAlexW2128736738WikidataQ58185687 ScholiaQ58185687MaRDI QIDQ2866197
Nicholas I. M. Gould, Coralia Cartis, Phillipe L. Toint
Publication date: 13 December 2013
Published in: SIAM Journal on Optimization (Search for Journal in Brave)
Full work available at URL: https://semanticscholar.org/paper/6f46d75c1ea1719f26ed995dfb722fa54d1c9ffa
On the complexity of solving feasibility problems with regularized models,
Unnamed Item,
Error bound conditions and convergence of optimization methods on smooth and proximally smooth manifolds,
A Stochastic Levenberg--Marquardt Method Using Random Models with Complexity Results,
Convergence and evaluation-complexity analysis of a regularized tensor-Newton method for solving nonlinear least-squares problems,
Worst-case evaluation complexity of a quadratic penalty method for nonconvex optimization,
Regularized Newton Method with Global \({\boldsymbol{\mathcal{O}(1/{k}^2)}}\) Convergence,
A Newton-CG Based Augmented Lagrangian Method for Finding a Second-Order Stationary Point of Nonconvex Equality Constrained Optimization with Complexity Guarantees,
A Trust Region Method for Finding Second-Order Stationarity in Linearly Constrained Nonconvex Optimization,
A structured diagonal Hessian approximation method with evaluation complexity analysis for nonlinear least squares,
Stochastic Conditional Gradient++: (Non)Convex Minimization and Continuous Submodular Maximization,
Complexity Analysis of a Trust Funnel Algorithm for Equality Constrained Optimization,
Corrigendum to: ``On the complexity of finding first-order critical points in constrained nonlinear optimization, Complexity of proximal augmented Lagrangian for nonconvex optimization with nonlinear equality constraints, Optimality of orders one to three and beyond: characterization and evaluation complexity in constrained nonconvex optimization, Regularized Newton Methods for Minimizing Functions with Hölder Continuous Hessians, A derivative-free trust-region algorithm for composite nonsmooth optimization, A brief survey of methods for solving nonlinear least-squares problems, Second-order optimality and beyond: characterization and evaluation complexity in convexly constrained nonlinear optimization, Approximately normalized iterative hard thresholding for nonlinear compressive sensing, Evaluation Complexity for Nonlinear Constrained Optimization Using Unscaled KKT Conditions and High-Order Models, Separable cubic modeling and a trust-region strategy for unconstrained minimization with impact in global optimization, Ghost Penalties in Nonconvex Constrained Optimization: Diminishing Stepsizes and Iteration Complexity, On the Evaluation Complexity of Constrained Nonlinear Least-Squares and General Constrained Nonlinear Optimization Using Second-Order Methods
