A simple illustration of interleaved learning using Kalman filter for linear least squares.

Interleaved learning Kalman filter Linear least squares

Journal

Results in applied mathematics
ISSN: 2590-0374
Titre abrégé: Results Appl Math
Pays: Netherlands
ID NLM: 9918733283106676

Informations de publication

Date de publication:
Nov 2023
Historique:
received: 21 09 2023
accepted: 03 11 2023
medline: 22 12 2023
pubmed: 22 12 2023
entrez: 22 12 2023
Statut: ppublish

Résumé

Interleaved learning in machine learning algorithms is a biologically inspired training method with promising results. In this short note, we illustrate the interleaving mechanism via a simple statistical and optimization framework based on Kalman Filter for Linear Least Squares.

Identifiants

pubmed: 38131008
doi: 10.1016/j.rinam.2023.100409
pii: S2590-0374(23)00055-9
pmc: PMC10734634
doi:

Types de publication

Journal Article

Langues

eng

Pagination

None

Informations de copyright

© 2023 The Author(s).

Déclaration de conflit d'intérêts

None.

Auteurs

Majnu John (M)

Departments of Mathematics and of Psychiatry, Hofstra University, Hempstead, NY, USA.
Feinstein Institutes of Medical Research, Northwell Health System, Manhasset, NY, USA.

Yihren Wu (Y)

Department of Mathematics, Hofstra University, Hempstead, NY, USA.

Classifications MeSH