Recent advances in error rate estimation
Pattern Recognition Letters
An atlas of functions
Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Introduction to the theory of neural computation
Introduction to the theory of neural computation
Small Sample Size Effects in Statistical Pattern Recognition: Recommendations for Practitioners
IEEE Transactions on Pattern Analysis and Machine Intelligence
COLT '91 Proceedings of the fourth annual workshop on Computational learning theory
Covariance pooling and stabilization for classification
Computational Statistics & Data Analysis
Neural Computation
A universal theorem on learning curves
Neural Networks
Rigorous learning curve bounds from statistical mechanics
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Statistical theory of learning curves under entropic loss criterion
Neural Computation
On linear discriminant analysis with adaptive ridge classification rules
Journal of Multivariate Analysis
The nature of statistical learning theory
The nature of statistical learning theory
Experimental study of performance of pattern classifiers and the size of design samples
Pattern Recognition Letters
Linear discrimination with adaptive ridge classification rules
Journal of Multivariate Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Expected classification error of the Fisher linear classifier with pseudo-inverse covariance matrix
Pattern Recognition Letters
Journal of Multivariate Analysis
How Bad May Learning Curves Be?
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical and neural classifiers: an integrated approach to design
Statistical and neural classifiers: an integrated approach to design
A Theory of Learning and Generalization: With Applications to Neural Networks and Control Systems
A Theory of Learning and Generalization: With Applications to Neural Networks and Control Systems
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Learning from Data: Concepts, Theory, and Methods
Learning from Data: Concepts, Theory, and Methods
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Estimation of Dependences Based on Empirical Data: Springer Series in Statistics (Springer Series in Statistics)
Expected Error of Minimum Empirical Error and Maximal Margin Classifiers
ICPR '96 Proceedings of the 13th International Conference on Pattern Recognition - Volume 2
Trainable fusion rules. II. Small sample-size effects
Neural Networks
Multi-agent System Approach to React to Sudden Environmental Changes
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
High-dimensional asymptotic expansions for the distributions of canonical correlations
Journal of Multivariate Analysis
Multicategory nets of single-layer perceptrons: complexity and sample-size issues
IEEE Transactions on Neural Networks
Balancing lifetime and classification accuracy of wireless sensor networks
Proceedings of the fourteenth ACM international symposium on Mobile ad hoc networking and computing
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Much work in discriminant analysis and statistical pattern recognition has been performed in the former Soviet Union. However, most results derived by former Soviet Union researchers are unknown to statisticians and statistical pattern recognition researchers in the West. We attempt to give a succinct overview of important contributions by Soviet Block researchers to several topics in the discriminant analysis literature concerning the small training-sample size problem. We also include a partial review of corresponding work done in the West.