A universal theorem on learning curves

Natural gradient works efficiently in learning

Neural Computation

Parameter convergence and learning curves for neural networks

Neural Computation

Credit Risk Assessment Using Statistical and MachineLearning: Basic Methodology and Risk Modeling Applications

Computational Economics - Computational Studies at Stanford

How Bad May Learning Curves Be?

IEEE Transactions on Pattern Analysis and Machine Intelligence

Algebraic geometrical methods for hierarchical learning machines

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Results in statistical discriminant analysis: a review of the former Soviet union literature

Journal of Multivariate Analysis

An asymptotic statistical theory of polynomial kernel methods

Neural Computation

An asymptotic statistical analysis of support vector machines with soft margins

Neural Networks

Algebraic Analysis for Nonidentifiable Learning Machines

Neural Computation

Nonmonotonic Generalization Bias of Gaussian Mixture Models

Neural Computation

Trainable fusion rules. II. Small sample-size effects

Neural Networks

Generalization error analysis for polynomial kernel methods: algebraic geometrical approach

ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing

Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in Singular Learning Theory

The Journal of Machine Learning Research

Generalization error of multinomial classifier

SSPR'06/SPR'06 Proceedings of the 2006 joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition

Generalization and learning error for nonlinear perceptron

Mathematical and Computer Modelling: An International Journal

Dreaming of mathematical neuroscience for half a century

Neural Networks