11 citations · 29 across the 15 of their papers we have counts for
5 papers · 1 filter
Adaptive First- and Second-Order Algorithms for Large-Scale Machine Learning
Sanae Lotfi, Tiphaine Bonniot de Ruisselet, Dominique Orban +1
In this paper, we consider both first- and second-order techniques to address continuous optimization problems arising in machine learning. In the first-order case, we propose a fr…
GPMR: An Iterative Method for Unsymmetric Partitioned Linear Systems
Alexis Montoison, Dominique Orban
We introduce an iterative method named GPMR for solving 2x2 block unsymmetric linear systems. GPMR is based on a new process that reduces simultaneously two rectangular matrices to…
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…
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…
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…