Zobrazeno 1 - 10
of 588
pro vyhledávání: '"Yang, Xiaoqi"'
In this paper we obtain a verifiable sufficient condition for a polyhedral multifunction to be Lipschitz continuous on its domain. We apply this sufficient condition to establish the Lipschitz continuity of the solution multifunction for an extended
Externí odkaz:
http://arxiv.org/abs/2406.16053
Autor:
Hong, Zesheng, Yue, Yubiao, Chen, Yubin, Cong, Lele, Lin, Huanjie, Luo, Yuanmei, Wang, Mini Han, Wang, Weidong, Xu, Jialong, Yang, Xiaoqi, Chen, Hechang, Li, Zhenzhang, Xie, Sihong
Computer-aided diagnostics has benefited from the development of deep learning-based computer vision techniques in these years. Traditional supervised deep learning methods assume that the test sample is drawn from the identical distribution as the t
Externí odkaz:
http://arxiv.org/abs/2404.18279
This paper addresses the study of novel constructions of variational analysis and generalized differentiation that are appropriate for characterizing robust stability properties of constrained set-valued mappings/multifunctions between Banach spaces
Externí odkaz:
http://arxiv.org/abs/2401.04907
We are concerned with structured $\ell_0$-norms regularization problems, with a twice continuously differentiable loss function and a box constraint. This class of problems have a wide range of applications in statistics, machine learning and image p
Externí odkaz:
http://arxiv.org/abs/2312.15718
The Kurdyka-{\L}ojasiewicz (K{\L}) property, exponent and modulus have played a very important role in the study of global convergence and rate of convergence for optimal algorithms. In this paper, at a stationary point of a locally lower semicontinu
Externí odkaz:
http://arxiv.org/abs/2308.15760
The paper concerns foundations of sensitivity and stability analysis, being primarily addressed constrained systems. We consider general models, which are described by multifunctions between Banach spaces and concentrate on characterizing their well-
Externí odkaz:
http://arxiv.org/abs/2212.02727
This paper is devoted to the study of a newly introduced tool, projectional coderivatives and the corresponding calculus rules in finite dimensions. We show that when the restricted set has some nice properties, more specifically, is a smooth manifol
Externí odkaz:
http://arxiv.org/abs/2210.11706
Autor:
Yao, Wenfang, Yang, Xiaoqi
This paper concerns upper estimates of the projectional coderivative of implicit mappings and corresponding applications on analyzing the relative Lipschitz-like property. Under different constraint qualifications, we provide upper estimates of the p
Externí odkaz:
http://arxiv.org/abs/2210.11335
This paper focuses on the minimization of a sum of a twice continuously differentiable function $f$ and a nonsmooth convex function. An inexact regularized proximal Newton method is proposed by an approximation to the Hessian of $f$ involving the $\v
Externí odkaz:
http://arxiv.org/abs/2209.09119