找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Population-Based Optimization on Riemannian Manifolds; Robert Simon Fong,Peter Tino Book 2022 The Editor(s) (if applicable) and The Author

[復(fù)制鏈接]
查看: 33708|回復(fù): 35
樓主
發(fā)表于 2025-3-21 17:26:02 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Population-Based Optimization on Riemannian Manifolds
編輯Robert Simon Fong,Peter Tino
視頻videohttp://file.papertrans.cn/752/751606/751606.mp4
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
叢書名稱Studies in Computational Intelligence
圖書封面Titlebook: Population-Based Optimization on Riemannian Manifolds;  Robert Simon Fong,Peter Tino Book 2022 The Editor(s) (if applicable) and The Author
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
關(guān)鍵詞Computational Intelligence; Population-based Optimization Algorithm; Riemannian Manifolds; Manifold Opt
版次1
doihttps://doi.org/10.1007/978-3-031-04293-5
isbn_softcover978-3-031-04295-9
isbn_ebook978-3-031-04293-5Series ISSN 1860-949X Series E-ISSN 1860-9503
issn_series 1860-949X
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

書目名稱Population-Based Optimization on Riemannian Manifolds影響因子(影響力)




書目名稱Population-Based Optimization on Riemannian Manifolds影響因子(影響力)學(xué)科排名




書目名稱Population-Based Optimization on Riemannian Manifolds網(wǎng)絡(luò)公開度




書目名稱Population-Based Optimization on Riemannian Manifolds網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Population-Based Optimization on Riemannian Manifolds被引頻次




書目名稱Population-Based Optimization on Riemannian Manifolds被引頻次學(xué)科排名




書目名稱Population-Based Optimization on Riemannian Manifolds年度引用




書目名稱Population-Based Optimization on Riemannian Manifolds年度引用學(xué)科排名




書目名稱Population-Based Optimization on Riemannian Manifolds讀者反饋




書目名稱Population-Based Optimization on Riemannian Manifolds讀者反饋學(xué)科排名




單選投票, 共有 0 人參與投票
 

0票 0%

Perfect with Aesthetics

 

0票 0%

Better Implies Difficulty

 

0票 0%

Good and Satisfactory

 

0票 0%

Adverse Performance

 

0票 0%

Disdainful Garbage

您所在的用戶組沒有投票權(quán)限
沙發(fā)
發(fā)表于 2025-3-21 23:13:31 | 只看該作者
第151606主題貼--第2樓 (沙發(fā))
板凳
發(fā)表于 2025-3-22 04:00:12 | 只看該作者
板凳
地板
發(fā)表于 2025-3-22 07:42:26 | 只看該作者
第4樓
5#
發(fā)表于 2025-3-22 12:42:48 | 只看該作者
5樓
6#
發(fā)表于 2025-3-22 16:15:24 | 只看該作者
6樓
7#
發(fā)表于 2025-3-22 19:39:35 | 只看該作者
7樓
8#
發(fā)表于 2025-3-23 00:57:21 | 只看該作者
8樓
9#
發(fā)表于 2025-3-23 01:28:12 | 只看該作者
9樓
10#
發(fā)表于 2025-3-23 08:31:44 | 只看該作者
10樓
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經(jīng)驗總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-20 02:33
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
哈巴河县| 吉安县| 胶南市| 杨浦区| 阿城市| 呼图壁县| 上饶县| 宣汉县| 铜鼓县| 宽甸| 株洲县| 宿州市| 永修县| 渑池县| 永顺县| 靖西县| 巴南区| 建水县| 天祝| 霍城县| 罗甸县| 贵定县| 开封市| 射阳县| 陕西省| 多伦县| 舒兰市| 永仁县| 宝坻区| 思南县| 沂水县| 阿巴嘎旗| 黄山市| 大埔区| 遵义市| 大埔区| 邮箱| 呼玛县| 汉中市| 固安县| 舒城县|