A statistical model of neural network learning via the Cramer-Rao lower bound

DOI10.1007/s42952-021-00122-8OpenAlexW3159242742MaRDI QIDQ2132021

Inho Park, Tae Yoon Kim

Publication date: 27 April 2022

Published in: Journal of the Korean Statistical Society (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s42952-021-00122-8

zbMATH Keywords

validationCramer-Rao lower boundANL algorithmstatistical NN learning modelstatistically successful NN learning

Mathematics Subject Classification ID

Computational learning theory (68Q32) Learning and adaptive systems in artificial intelligence (68T05)

Uses Software

• MASS (R)
• neuralnet
• ISLR
• RSNNS

Cites Work

• What is a universal computing machine?
• Mathematical statistics. An introduction
• Multilayer feedforward networks are universal approximators
• On the computational power of neural nets
• Statistical Analysis of Financial Data in S-Plus
• An Introduction to Statistical Learning

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