| 书目名称 | Population-Based Optimization on Riemannian Manifolds |
| 编辑 | Robert Simon Fong,Peter Tino |
| 视频video | |
| 概述 | Presents recent research on Population-based Optimization on Riemannian manifolds.Addresses the locality and implicit assumptions of manifold optimization.Presents a novel population-based optimizatio |
| 丛书名称 | Studies in Computational Intelligence |
| 图书封面 |  |
| 描述 | .Manifold optimization is an emerging field of contemporary optimization that constructs efficient and robust algorithms by exploiting the specific geometrical structure of the search space. In our case the search space takes the form of a manifold. .Manifold optimization methods mainly focus on adapting existing optimization methods from the usual “easy-to-deal-with” Euclidean search spaces to manifolds whose local geometry can be defined e.g. by a Riemannian structure. In this way the form of the adapted algorithms can stay unchanged. However, to accommodate the adaptation process, assumptions on the search space manifold often have to be made. In addition, the computations and estimations are confined by the local geometry..This book presents a framework for population-based optimization on Riemannian manifolds that overcomes both the constraints of locality and additional assumptions. Multi-modal, black-box manifold optimization problems on Riemannian manifolds can be tackled using zero-order stochastic optimization methods from a geometrical perspective, utilizing both the statistical geometry of the decision space and Riemannian geometry of the search space..This monograph pr |
| 出版日期 | Book 2022 |
| 关键词 | Computational Intelligence; Population-based Optimization Algorithm; Riemannian Manifolds; Manifold Opt |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-031-04293-5 |
| isbn_softcover | 978-3-031-04295-9 |
| isbn_ebook | 978-3-031-04293-5Series ISSN 1860-949X Series E-ISSN 1860-9503 |
| issn_series | 1860-949X |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
发表于 2025-3-21 17:26:02
