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01.12.2023 | SCIENTIFIC SCHOOLS OF THE KRASOVSKII INSTITUTE OF MATHEMATICS AND MECHANICS OF THE URAL BRANCH OF THE RUSSIAN ACADEMY OF SCIENCES, YEKATERINBURG, THE RUSSIAN FEDERATION

Ural School of Pattern Recognition: Majoritarian Approach to Ensemble Learning

verfasst von: Vl. D. Mazurov, M. I. Poberii, M. Yu. Khachai

Erschienen in: Pattern Recognition and Image Analysis | Ausgabe 4/2023

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Abstract

This article provides an overview of the significant achievements of the Ural School of Pattern Recognition. The focus is on majoritarian generalized solutions for algebraic equations and inequalities that may not always adhere to standard properties. The paper also delves into the broader applications of these findings in collective machine learning techniques. In the literature, these generalized solutions are frequently referred to as committee generalized solutions or simply committees, leading to the derived learning methods being called committee machines. Our discussion primarily centers on the foundational theorems confirming the existence of such solutions, the intricacies of combinatorial optimization during their exploration, and the subsequent emergence of collective machine learning algorithms.

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We believe that the number 0 is coprime with any natural number.

In which matching feature descriptions of objects x_i = x_j implies matching labels y_i = y_j, indicating their class affiliation.

It belongs to the class of combinatorial optimization tasks, having polynomial-time approximation algorithms with constant approximation factors.

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Titel: Ural School of Pattern Recognition: Majoritarian Approach to Ensemble Learning
verfasst von: Vl. D. Mazurov
M. I. Poberii
M. Yu. Khachai
Publikationsdatum: 01.12.2023
Verlag: Pleiades Publishing
Erschienen in: Pattern Recognition and Image Analysis / Ausgabe 4/2023
Print ISSN: 1054-6618
Elektronische ISSN: 1555-6212
DOI: https://doi.org/10.1134/S1054661823040314

SCIENTIFIC SCHOOLS OF THE FEDERAL RESEARCH CENTER “COMPUTER SCIENCE AND CONTROL” OF THE RUSSIAN ACADEMY OF SCIENCES, MOSCOW, THE RUSSIAN FEDERATION

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