Restricted Boltzmann Machine Assignment Algorithm: Application to solve many-to-one matching problems on weighted bipartite graph
Optimization and Control
2019-05-03 v2 Machine Learning
Machine Learning
Abstract
In this work an iterative algorithm based on unsupervised learning is presented, specifically on a Restricted Boltzmann Machine (RBM) to solve a perfect matching problem on a bipartite weighted graph. Iteratively is calculated the weights and the bias parameters that maximize the energy function and assignment element to element . An application of real problem is presented to show the potentiality of this algorithm.
Cite
@article{arxiv.1904.13111,
title = {Restricted Boltzmann Machine Assignment Algorithm: Application to solve many-to-one matching problems on weighted bipartite graph},
author = {Francesco Curia},
journal= {arXiv preprint arXiv:1904.13111},
year = {2019}
}
Comments
In this version is was update the thresholds determination