Zobrazeno 1 - 10
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pro vyhledávání: '"Local and global convergence"'
Autor:
Nesterov, Yurii
In the first part of this paper, we prove that, under some natural non-degeneracy assumptions, the Greedy Parabolic Target-Following Method, based on {\em universal tangent direction} has a favorable local behavior. In view of its global complexity b
Externí odkaz:
http://arxiv.org/abs/2412.14934
Akademický článek
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Autor:
Li, Shuang, Li, Qiuwei
Tensor optimization is crucial to massive machine learning and signal processing tasks. In this paper, we consider tensor optimization with a convex and well-conditioned objective function and reformulate it into a nonconvex optimization using the Bu
Externí odkaz:
http://arxiv.org/abs/2201.02298
Akademický článek
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The article discusses distributed gradient-descent algorithms for computing local and global minima in nonconvex optimization. For local optimization, we focus on distributed stochastic gradient descent (D-SGD)--a simple network-based variant of clas
Externí odkaz:
http://arxiv.org/abs/2003.10309
Autor:
Kwon, Seong-Ho, Ahn, Hyo-Sung
This paper discusses generalized weak rigidity theory, and aims to apply the theory to formation control problems with a gradient flow law. The generalized weak rigidity theory is utilized in order that desired formations are characterized by a gener
Externí odkaz:
http://arxiv.org/abs/1809.02562
Autor:
Johnstone, Patrick R., Moulin, Pierre
Publikováno v:
Comput Optim Appl 67, 259-292 (2017)
This paper is concerned with convex composite minimization problems in a Hilbert space. In these problems, the objective is the sum of two closed, proper, and convex functions where one is smooth and the other admits a computationally inexpensive pro
Externí odkaz:
http://arxiv.org/abs/1602.02726
Autor:
Johnstone, Patrick R., Moulin, Pierre
A problem of great interest in optimization is to minimize a sum of two closed, proper, and convex functions where one is smooth and the other has a computationally inexpensive proximal operator. In this paper we analyze a family of Inertial Forward-
Externí odkaz:
http://arxiv.org/abs/1502.02281
Autor:
Johnstone, Patrick1 prjohns2@illinois.edu, Moulin, Pierre1 moulin@ifp.uiuc.edu
Publikováno v:
Computational Optimization & Applications. Jun2017, Vol. 67 Issue 2, p259-292. 34p.
