Add to ORKGThis dissertation describes optimization methods and matrix factorizations for large-scale quasi-Newton trust-region methods. The proposed methods are applicable to convex and non-convex optimization problems, and are described in algorithms for software implementations
The trust-region subproblem of minimizing a quadratic function subject to a norm constraint arises i...
Newton's method plays a central role in the development of numerical techniques for optimization. In...
Trust region algorithms are a class of recently developed algorithms for solving optimization proble...
Includes bibliographical references (l. 37).This project presents a new approach to Quasi-Newton met...
We present a new Newton-like method for large-scale unconstrained nonconvex minimization. And a new ...
Limited-memory quasi-Newton methods and trust-region methods represent two efficient approaches used...
Limited memory quasi-Newton methods and trust-region methods represent two efficient approaches used...
The solution of trust-region and regularisation subproblems which arise in unconstrained optimizatio...
.<F3.833e+05> This paper describes a software implementation of Byrd and Omojokun's trust...
Abstract. We consider methods for large-scale unconstrained minimization based on finding an approxi...
In this work, we consider methods for large-scale and nonconvex unconstrained optimization. We propo...
Trust-region methods are amongst the most commonly used methods in unconstrained mathematical optimi...
The trust-region subproblem of minimizing a quadratic function subject to a norm constraint arises i...
The trust-region subproblem of minimizing a quadratic function subject to a norm constraint arises i...
We consider a family of dense initializations for limited-memory quasi-Newton methods. The proposed ...
The trust-region subproblem of minimizing a quadratic function subject to a norm constraint arises i...
Newton's method plays a central role in the development of numerical techniques for optimization. In...
Trust region algorithms are a class of recently developed algorithms for solving optimization proble...
Includes bibliographical references (l. 37).This project presents a new approach to Quasi-Newton met...
We present a new Newton-like method for large-scale unconstrained nonconvex minimization. And a new ...
Limited-memory quasi-Newton methods and trust-region methods represent two efficient approaches used...
Limited memory quasi-Newton methods and trust-region methods represent two efficient approaches used...
The solution of trust-region and regularisation subproblems which arise in unconstrained optimizatio...
.<F3.833e+05> This paper describes a software implementation of Byrd and Omojokun's trust...
Abstract. We consider methods for large-scale unconstrained minimization based on finding an approxi...
In this work, we consider methods for large-scale and nonconvex unconstrained optimization. We propo...
Trust-region methods are amongst the most commonly used methods in unconstrained mathematical optimi...
The trust-region subproblem of minimizing a quadratic function subject to a norm constraint arises i...
The trust-region subproblem of minimizing a quadratic function subject to a norm constraint arises i...
We consider a family of dense initializations for limited-memory quasi-Newton methods. The proposed ...
The trust-region subproblem of minimizing a quadratic function subject to a norm constraint arises i...
Newton's method plays a central role in the development of numerical techniques for optimization. In...
Trust region algorithms are a class of recently developed algorithms for solving optimization proble...