Spectral projected gradient methods: review and perspectives
Over the last two decades, it has been observed that using the gradient vector as a search
direction in large-scale optimization may lead to efficient algorithms. The effectiveness relies …
direction in large-scale optimization may lead to efficient algorithms. The effectiveness relies …
[图书][B] Practical augmented Lagrangian methods for constrained optimization
EG Birgin, JM Martínez - 2014 - SIAM
This book is about the Augmented Lagrangian method, a popular technique for solving
constrained optimization problems. It is mainly dedicated to engineers, chemists, physicists …
constrained optimization problems. It is mainly dedicated to engineers, chemists, physicists …
SPF-GMKL: generalized multiple kernel learning with a million kernels
Multiple Kernel Learning (MKL) aims to learn the kernel in an SVM from training data. Many
MKL formulations have been proposed and some have proved effective in certain …
MKL formulations have been proposed and some have proved effective in certain …
Quadratic regularization projected Barzilai–Borwein method for nonnegative matrix factorization
Y Huang, H Liu, S Zhou - Data mining and knowledge discovery, 2015 - Springer
In this paper, based on the alternating nonnegative least squares framework, we present a
new efficient method for nonnegative matrix factorization that uses a quadratic regularization …
new efficient method for nonnegative matrix factorization that uses a quadratic regularization …
A Barzilai-Borwein type method for minimizing composite functions
Y Huang, H Liu - Numerical Algorithms, 2015 - Springer
In this paper, we propose a Barzilai-Borwein (BB) type method for minimizing the sum of a
smooth function and a convex but possibly nonsmooth function. At each iteration, our …
smooth function and a convex but possibly nonsmooth function. At each iteration, our …
On the rate of convergence of projected Barzilai–Borwein methods
Y Huang, H Liu - Optimization Methods and Software, 2015 - Taylor & Francis
We study the rate of convergence of a projected Barzilai–Borwein method, which performs
the Grippo–Lampariello–Lucidi (GLL) non-monotone line search along the feasible …
the Grippo–Lampariello–Lucidi (GLL) non-monotone line search along the feasible …
Inexact variable metric method for convex-constrained optimization problems
DS Gonçalves, MLN Gonçalves, TC Menezes - Optimization, 2022 - Taylor & Francis
This paper is concerned with the inexact variable metric method for solving convex-
constrained optimization problems. At each iteration of this method, the search direction is …
constrained optimization problems. At each iteration of this method, the search direction is …
[PDF][PDF] Aplicação do método do gradiente espectral projetado ao problema de compressive sensing
BC Llave - 2012 - academia.edu
A teoria de Compressive Sensing proporciona uma nova estratégia de aquisição e
recuperação de dados com bons resultados na área de processamento de imagens. Esta …
recuperação de dados com bons resultados na área de processamento de imagens. Esta …
Quantum algorithms with tensor approach
L Gu - 2020 - theses.lib.polyu.edu.hk
Recently quantum computing becomes more and more popular and realizable, and tensor is
an effective method in quantum computing. This thesis is devoted to studying structured …
an effective method in quantum computing. This thesis is devoted to studying structured …
Preconditioning ideas for the Augmented Lagrangian method
AM Sajo-Castelli - arXiv preprint arXiv:1702.07196, 2017 - arxiv.org
A preconditioning strategy for the Powell-Hestenes-Rockafellar Augmented Lagrangian
method (ALM) is presented. The scheme exploits the structure of the Augmented Lagrangian …
method (ALM) is presented. The scheme exploits the structure of the Augmented Lagrangian …