Home >

news ヘルプ

論文・著書情報


タイトル
和文: 
英文:Generalized left-localized Cayley parametrization for optimization with orthogonality constraints 
著者
和文: 久米 啓太, 山田 功.  
英文: Keita Kume, Isao Yamada.  
言語 English 
掲載誌/書名
和文: 
英文:Optimization 
巻, 号, ページ        
出版年月 2022年11月15日 
出版者
和文: 
英文: 
会議名称
和文: 
英文: 
開催地
和文: 
英文: 
DOI https://doi.org/10.1080/02331934.2022.2142471
アブストラクト We present a reformulation of optimization problems over the Stiefel manifold by using a Cayley-type transform, named the generalized left-localized Cayley transform, for the Stiefel manifold. The reformulated optimization problem is defined over a vector space, whereby we can apply directly powerful computational arts designed for optimization over a vector space. The proposed Cayley-type transform enjoys several key properties which are useful to (i) study relations between the original problem and the proposed problem; (ii) check the conditions to guarantee the global convergence of optimization algorithms. Numerical experiments demonstrate that the proposed algorithm outperforms the standard algorithms designed with a retraction on the Stiefel manifold.

©2007 Institute of Science Tokyo All rights reserved.