Eigenvalue problem approach to discrete minimization

Authors:
Leonid B. Litinskii
Affiliations:
Institute of Optical Neural Technologies Russian Academy of Sciences, Moscow, Russia
Venue:
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Year:
2005

Citing 3
Cited 1

Introduction to the theory of neural computation

Introduction to the theory of neural computation
Neural Networks for Combinatorial Optimization: a Review of More Than a Decade of Research

INFORMS Journal on Computing
New Optimization Algorithms in Physics

New Optimization Algorithms in Physics

Binary minimization: increasing the attraction area of the global minimum in the binary optimization problem

ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part II

Quantified Score

Hi-index	0.00

Visualization

Abstract

The problem of finding of the deepest local minimum of a quadratic functional of binary variables is discussed. Our approach is based on the asynchronous neural dynamics and utilizes the eigenvalues and eigenvectors of the connection matrix. We discuss the role of the largest eigenvalues. We report the results of intensive computer experiments with random matrices of large dimensions N ∼ 102 - 103.