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20192022
most citedStochastic Damped L-BFGS with Controlled Norm of the Hessian Approximation

2 citations · 3 across the 5 of their papers we have counts for

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7 papers · 1 filter

math.OC2022

Computing a Sparse Projection into a Box

Dominique Orban

We describe a procedure to compute a projection of into the intersection of the so-called \emph{zero-norm} ball of radius , i.e., the set o…

math.OC20211 cited

Scalable adaptive cubic regularization methods

Jean-Pierre Dussault, Dominique Orban

Adaptive cubic regularization (ARC) methods for unconstrained optimization compute steps from linear systems involving a shifted Hessian in the spirit of the Levenberg-Marquardt an…

math.OC2021

A Proximal Quasi-Newton Trust-Region Method for Nonsmooth Regularized Optimization

Aleksandr Y. Aravkin, Robert Baraldi, Dominique Orban

We develop a trust-region method for minimizing the sum of a smooth term and a nonsmooth term ), both of which can be nonconvex. Each iteration of our method minimizes a pos…

math.OC2021

A Julia implementation of Algorithm NCL for constrained optimization

Ding Ma, Dominique Orban, Michael A. Saunders

Algorithm NCL is designed for general smooth optimization problems where first and second derivatives are available, including problems whose constraints may not be linearly indepe…

math.OC2020

Scaled Projected-Directions Methods with Application to Transmission Tomography

Guillaume Mestdagh, Yves Goussard, Dominique Orban

Statistical image reconstruction in X-Ray computed tomography yields large-scale regularized linear least-squares problems with nonnegativity bounds, where the memory footprint of…

math.OC2019

Implementing a smooth exact penalty function for general constrained nonlinear optimization

Ron Estrin, Michael Friedlander, Dominique Orban +1

We build upon Estrin et al. (2019) to develop a general constrained nonlinear optimization algorithm based on a smooth penalty function proposed by Fletcher (1970, 1973b). Although…