From Statistics to Neural Networks

Alternate Titles

• Proceedings of the NATO Advances Study Institute From Statistics to Neural Networks, Theory and Pattern Recognition Applications, held in Les Arcs, Bourg Saint Maurice, France, June 21 - July 2, 1993

Description

This volume provides a unified approach to the study of predictive learning, i.e., generalization from examples. It contains an up-to-date review and in-depth treatment of major issues and methods related to predictive learning in statistics, Artificial Neural Networks (ANN), and pattern recognition. Topics range from theoretical modeling and adaptive computational methods to empirical comparisons between statistical and ANN methods, and applications. Most contributions fall into one of the three themes: unified framework for the study of predictive learning in statistics and ANNs; similarities and differences between statistical and ANN methods for nonparametric estimation (learning); and fundamental connections between artificial and biological learning systems.

Subjects

Series Statement

• NATO ASI Series, Series F: Computer and Systems Sciences -- 136
• NATO ASI series -- 136.

Links

• SpringerLink

Other Editions

• From Statistics to Neural Networks: Theory and Pattern Recognition ApplicationsElectronic resourceSpringer Berlin Heidelberg1994-01-01
• From Statistics to Neural NetworksIsland Press1994-01-01
• From Statistics to Neural NetworksPaperbackSpringer2011-12-22