Add to ORKGThis paper proposes a modified BFGS formula using a trust region model for solving non-smooth convex minimizations by using the Moreau-Yosida regularization (smoothing) approach and a new secant equation with a BFGS update formula. Our algorithm uses the function value information and gradient value information to compute the Hessian. The Hes-sian matrix is updated by the BFGS formula rather than using second-order information of the function, thus decreasing the workload and time involved in the computation. Under suit-able conditions, the algorithm converges globally to an optimal solution. Numerical results show that this algorithm can successfully solve nonsmooth unconstrained convex problems
We introduce a new method for solving a nonsmooth unconstrained optimization problem. This method is...
In this paper, a Riemannian BFGS method for minimizing a smooth function on a Riemannian manifold is...
Abstract. We investigate the BFGS algorithm with an inexact line search when applied to non-smooth f...
This paper proposes a modified BFGS formula using a trust region model for solving nonsmooth convex ...
. We propose an implementable BFGS method for solving a nonsmooth convex optimization problem by con...
In establishing global convergence results for trust region algorithms applied to unconstrained opti...
summary:Trust region methods are a class of effective iterative schemes in numerical optimization. I...
We introduce a trust region algorithm for minimization of nonsmooth functions with linear constraint...
This paper investigates the potential behavior, both good and bad, of the well-known BFGS algorithm ...
Regularized minimization problems with nonconvex, nonsmooth, perhaps non-Lipschitz penalty functions...
A general family of trust region algorithms for nonsmooth optimization is considered. Conditions for...
The BFGS method is one of the most effective quasi-Newton algorithms for minimization-optimization p...
Abstract In this paper, a modified BFGS algorithm is proposed for unconstrained optimization. The pr...
We extend the well-known BFGS quasi-Newton method and its memory-limited variant LBFGS to the optimi...
An improved trust region method for unconstrained optimization Jun Liu In this paper, a new trust re...
We introduce a new method for solving a nonsmooth unconstrained optimization problem. This method is...
In this paper, a Riemannian BFGS method for minimizing a smooth function on a Riemannian manifold is...
Abstract. We investigate the BFGS algorithm with an inexact line search when applied to non-smooth f...
This paper proposes a modified BFGS formula using a trust region model for solving nonsmooth convex ...
. We propose an implementable BFGS method for solving a nonsmooth convex optimization problem by con...
In establishing global convergence results for trust region algorithms applied to unconstrained opti...
summary:Trust region methods are a class of effective iterative schemes in numerical optimization. I...
We introduce a trust region algorithm for minimization of nonsmooth functions with linear constraint...
This paper investigates the potential behavior, both good and bad, of the well-known BFGS algorithm ...
Regularized minimization problems with nonconvex, nonsmooth, perhaps non-Lipschitz penalty functions...
A general family of trust region algorithms for nonsmooth optimization is considered. Conditions for...
The BFGS method is one of the most effective quasi-Newton algorithms for minimization-optimization p...
Abstract In this paper, a modified BFGS algorithm is proposed for unconstrained optimization. The pr...
We extend the well-known BFGS quasi-Newton method and its memory-limited variant LBFGS to the optimi...
An improved trust region method for unconstrained optimization Jun Liu In this paper, a new trust re...
We introduce a new method for solving a nonsmooth unconstrained optimization problem. This method is...
In this paper, a Riemannian BFGS method for minimizing a smooth function on a Riemannian manifold is...
Abstract. We investigate the BFGS algorithm with an inexact line search when applied to non-smooth f...