Results 21 to 30 of about 7,447,344 (290)
Global Optimality in Low-Rank Matrix Optimization [PDF]
This paper considers the minimization of a general objective function $f(X)$ over the set of rectangular $n\times m$ matrices that have rank at most $r$. To reduce the computational burden, we factorize the variable $X$ into a product of two smaller matrices and optimize over these two matrices instead of $X$. Despite the resulting nonconvexity, recent
Zhihui Zhu +3 more
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Neural Network Algorithm with Dropout Using Elite Selection
A neural network algorithm is a meta-heuristic algorithm inspired by an artificial neural network, which has a strong global search ability and can be used to solve global optimization problems.
Yong Wang, Kunzhao Wang, Gaige Wang
doaj +1 more source
Diffusions for Global Optimization
We seek a global minimum of $U:[0,1]^n \to R$. The solution to $({d / {dt}})x_t = - \nabla U(x_t )$ will find local minima. The solution to $dx_t = - \nabla U(x_t )dt + \sqrt {2T} dw_t $, where w is standard (n-dimensional) Brownian motion and the boundaries are reflecting, will concentrate near the global minima of U, at least when “temperature” T is ...
Geman, Stuart, Hwang, Chii-Ruey
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Agent-based Optimization of Advisory Strategy Parameters
In this paper, an application of Evolutionary Multiagent Systems (EMAS) and its memetic version to the optimization of advisory strategy (in this case, Sudoku advisory strategy) is considered.
Mateusz Polnik +2 more
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Biased random-key genetic algorithm for bound-constrained global optimization [PDF]
Global optimization seeks a minimum or maximum of a multimodal function over a discrete or continuous domain. In this paper, we propose a biased random-key genetic algorithm for finding approximate solutions for continuous global optimization problems ...
R. M. A. Silva +3 more
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This study delves into the automatic analog circuit design, focusing primarily on topology optimization. Many real-world calculations and evaluations often involve complex and nonlinear problems, posing significant challenges in optimization.
Masaharu HIDA +4 more
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Machine learning for global optimization [PDF]
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
CASSIOLI, ANDREA +4 more
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3D NoC Low-Power Mapping Optimization Based on Improved Genetic Algorithm
Power optimization is an important part of network-on-chip(NoC) design. This paper proposes an improved algorithm based on genetic algorithm on how to properly map IP (Intellectual Property) cores to 3D NoC.
Yu Gan, Hong Guo, Ziheng Zhou
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Thermodynamics of Global Optimization
Theoretical design of global optimization algorithms can profitably utilize recent statistical mechanical treatments of potential energy surfaces (PES's). Here we analyze a particular method to explain its success in locating global minima on surfaces with a multiple-funnel structure, where trapping in local minima with different morphologies is ...
Doye, J, Wales, D
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Global descent methods for unconstrained global optimization
Global descent method, Global optimization, Local search, Modified function approach, Non-convex optimization,
D. Li +7 more
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