Now showing items 1-10 of 1079
Theory of machine learning based on nonrelativistic quantum mechanics
(World ScientificPE, 2021)
The goal of this paper is the presentation of the elementary procedures that normally are done in nonrelativistic Quantum Mechanics in terms of the principles of Machine Learning. In essence, this paper discusses Mitchell's ...
Nota del Editor
(Universidad de Palermo, 2021)
Testing Machine Learning at Classical Electrodynamics
(Institute of Electrical and Electronics EngineersPE, 2021-10-22)
Like physics or another laws-based basic science, machine learning might also be a firm methodology to solve physics problems by the which a kind of optimization and minimization of energy are needed. Expressed at the ...
Machine Learning As an Advanced Algorithm To Solve Optimization Problems in Physics
(Institute of Electrical and Electronics EngineersPE, 2021-08-19)
It is argued that the standard procedures to solve problems in physics particularly in the field of electrodynamics have in a tacit manner the actions of Machine Learning, such as the criteria of Tom Mitchell, (i) task, ...
Machine Learning Methods with Noisy, Incomplete or Small Datasets
In this article, we present a collection of fifteen novel contributions on machine learning methods with low-quality or imperfect datasets, which were accepted for publication in the special issue “Machine Learning Methods ...
APRENDIZAJE AUTOMÁTICO, INTELIGENCIA (AI Y HI) Y APRENDIZAJE EN REDES DIGITALESMACHINE LEARNING, INTELLIGENCE (AI AND HI) AND LEARNING ON DIGITAL NETWORKS
(Universidad Nacional de Educación, 2019)
Machine Learning to Assess Urbanistic Development in the South Pole of Lima City
We employ Machine Learning through the Mitchell’s criteria to carry out an assessment on the potential spatial configurations at the south pole of Lima city, at Perú. Based at both qualitative and quantitative facts, an ...