High-Dimensional Separability for One- and Few-Shot Learning

High-Dimensional Separability for One- and Few-Shot Learning

This work is driven by a practical question: corrections of Artificial Intelligence (AI) errors. These corrections should be quick and non-iterative. To solve this problem without modification of a legacy AI system, we propose special ‘external’ devices, correctors. Elementary correctors consist of...

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Bibliographic Details
Main Authors: Alexander N. Gorban, Bogdan Grechuk, Evgeny M. Mirkes, Sergey V. Stasenko, Ivan Y. Tyukin
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Entropy
Subjects:
Artificial Intelligence
blessing of dimensionality
clusters
errors
separability
discriminant
Online Access:https://www.mdpi.com/1099-4300/23/8/1090

Internet

https://www.mdpi.com/1099-4300/23/8/1090

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