2013-2014 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe
The analysis of gradient descent-type methods typically relies on the Lipschitz continuity of the ob...
Convexity is an essential characteristic in optimization. In reality, many optimization problems are...
Convexity is an essential characteristic in optimization. In reality, many optimization problems are...
Regularized minimization problems with nonconvex, nonsmooth, perhaps non-Lipschitz penalty functions...
We establish or refute the optimality of inexact second-order methods for unconstrained nonconvex op...
We establish or refute the optimality of inexact second-order methods for unconstrained nonconvex op...
2013-2014 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe
We propose a novel trust region method for solving a class of nonsmooth, nonconvex composite-type op...
We introduce a trust region algorithm for minimization of nonsmooth functions with linear constraint...
We introduce a trust region algorithm for minimization of nonsmooth functions with linear constraint...
We introduce a trust region algorithm for minimization of nonsmooth functions with linear constraint...
An adaptive regularization algorithm using inexact function and derivatives evaluations is proposed ...
The minimization of a particular nondifferentiable function is considered. The first and second orde...
We consider variants of trust-region and adaptive cubic regularization methods for non-convex optimi...
© Springer Science+Business Media, LLC, part of Springer Nature 2019. This is a post-peer-review, pr...
The analysis of gradient descent-type methods typically relies on the Lipschitz continuity of the ob...
Convexity is an essential characteristic in optimization. In reality, many optimization problems are...
Convexity is an essential characteristic in optimization. In reality, many optimization problems are...
Regularized minimization problems with nonconvex, nonsmooth, perhaps non-Lipschitz penalty functions...
We establish or refute the optimality of inexact second-order methods for unconstrained nonconvex op...
We establish or refute the optimality of inexact second-order methods for unconstrained nonconvex op...
2013-2014 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe
We propose a novel trust region method for solving a class of nonsmooth, nonconvex composite-type op...
We introduce a trust region algorithm for minimization of nonsmooth functions with linear constraint...
We introduce a trust region algorithm for minimization of nonsmooth functions with linear constraint...
We introduce a trust region algorithm for minimization of nonsmooth functions with linear constraint...
An adaptive regularization algorithm using inexact function and derivatives evaluations is proposed ...
The minimization of a particular nondifferentiable function is considered. The first and second orde...
We consider variants of trust-region and adaptive cubic regularization methods for non-convex optimi...
© Springer Science+Business Media, LLC, part of Springer Nature 2019. This is a post-peer-review, pr...
The analysis of gradient descent-type methods typically relies on the Lipschitz continuity of the ob...
Convexity is an essential characteristic in optimization. In reality, many optimization problems are...
Convexity is an essential characteristic in optimization. In reality, many optimization problems are...
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