2026-06-27T16:26:22Zhttps://docta.ucm.es/rest/oai/requestoai:docta.ucm.es:20.500.14352/74962024-02-26T15:17:21Zcom_20.500.14352_14col_20.500.14352_15
Docta Complutense
author
Gorban, Alexander N.
author
Makarov Slizneva, Valeriy
author
Tyukin, Ivan Y.
2023-06-17T08:55:33Z
2023-06-17T08:55:33Z
2020-01-09
1099-4300
10.3390/e22010082
https://hdl.handle.net/20.500.14352/7496
https://doi.org/10.3390/e22010082
https://www.mdpi.com/1099-4300/22/1/82
High-dimensional data and high-dimensional representations of reality are inherent features of modern Artificial Intelligence systems and applications of machine learning. The well-known phenomenon of the “curse of dimensionality” states: many problems become exponentially difficult in high dimensions. Recently, the other side of the coin, the “blessing of dimensionality”, has attracted much attention. It turns out that generic high-dimensional datasets exhibit fairly simple geometric properties. Thus, there is a fundamental tradeoff between complexity and simplicity in high dimensional spaces. Here we present a brief explanatory review of recent ideas, results and hypotheses about the blessing of dimensionality and related simplifying effects relevant to machine learning and neuroscience.
eng
Atribución 3.0 España
High-Dimensional Brain in a High-Dimensional World: Blessing of Dimensionality
journal article
URL
https://docta.ucm.es/bitstreams/941441a2-8599-4e74-aff7-934b09064f90/download
File
MD5
eb8fe0f85f423b1aad655f33acb020dc
906110
application/pdf
makarov105.pdf