[HTML][HTML] Two decades of blackbox optimization applications
This article reviews blackbox optimization applications of direct search optimization methods
over the past twenty years. Emphasis is placed on the Mesh Adaptive Direct Search (Mads) …
over the past twenty years. Emphasis is placed on the Mesh Adaptive Direct Search (Mads) …
[图书][B] Introduction: tools and challenges in derivative-free and blackbox optimization
In this introductory chapter, we present a high-level description of optimization, blackbox
optimization, and derivative-free optimization. We introduce some basic optimization …
optimization, and derivative-free optimization. We introduce some basic optimization …
[图书][B] Riemannian optimization and its applications
H Sato - 2021 - Springer
Mathematical optimization is an important branch of applied mathematics. Different classes
of optimization problems are categorized based on their problem structures. While there are …
of optimization problems are categorized based on their problem structures. While there are …
A collection of nonsmooth Riemannian optimization problems
PA Absil, S Hosseini - Nonsmooth optimization and its applications, 2019 - Springer
Nonsmooth Riemannian optimization is still a scarcely explored subfield of optimization
theory that concerns the general problem of minimizing (or maximizing) over a domain …
theory that concerns the general problem of minimizing (or maximizing) over a domain …
Robust optimization of noisy blackbox problems using the mesh adaptive direct search algorithm
C Audet, A Ihaddadene, S Le Digabel, C Tribes - Optimization Letters, 2018 - Springer
Blackbox optimization problems are often contaminated with numerical noise, and direct
search methods such as the Mesh Adaptive Direct Search (MADS) algorithm may get stuck …
search methods such as the Mesh Adaptive Direct Search (MADS) algorithm may get stuck …
Riemannian Smoothing Gradient Type Algorithms for Nonsmooth Optimization Problem on Compact Riemannian Submanifold Embedded in Euclidean Space
In this paper, we introduce the notion of generalized ϵ-stationarity for a class of nonconvex
and nonsmooth composite minimization problems on compact Riemannian submanifold …
and nonsmooth composite minimization problems on compact Riemannian submanifold …
[PDF][PDF] Riemannian smoothing gradient type algorithms for nonsmooth optimization problem on manifolds
In this paper, we introduce the notion of generalized ǫ-stationarity for a class of nonconvex
and nonsmooth composite minimization problems on Riemannian manifolds embedding in …
and nonsmooth composite minimization problems on Riemannian manifolds embedding in …
Linear equalities in blackbox optimization
C Audet, S Le Digabel, M Peyrega - Computational Optimization and …, 2015 - Springer
The mesh adaptive direct search (Mads) algorithm is designed for blackbox optimization
problems subject to general inequality constraints. Currently, Mads does not support …
problems subject to general inequality constraints. Currently, Mads does not support …
Local difference ternary sequences descriptor based on unsupervised min redundancy mutual information feature selection
G Tao, Z Liu, J Cao, S Liang - Multidimensional Systems and Signal …, 2020 - Springer
Texture feature description research have received significant attention in recent years. It is
widely known that the local texture feature descriptor can achieve good performance under …
widely known that the local texture feature descriptor can achieve good performance under …
Range-based ICA using a nonsmooth quasi-Newton optimizer for electroencephalographic source localization in focal epilepsy
Independent component analysis (ICA) aims at separating a multivariate signal into
independent nongaussian signals by optimizing a contrast function with no knowledge on …
independent nongaussian signals by optimizing a contrast function with no knowledge on …