Training knowledge-based neural networks to recognize genes in DNA sequences
NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
Ten lectures on wavelets
Independent component analysis, a new concept?
Signal Processing - Special issue on higher order statistics
The nature of statistical learning theory
The nature of statistical learning theory
Computational intelligence PC tools
Computational intelligence PC tools
The Geometry of Algorithms with Orthogonality Constraints
SIAM Journal on Matrix Analysis and Applications
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
Better Prediction of Protein Cellular Localization Sites with the it k Nearest Neighbors Classifier
Proceedings of the 5th International Conference on Intelligent Systems for Molecular Biology
Introduction to Stochastic Search and Optimization
Introduction to Stochastic Search and Optimization
Kernel Independent Component Analysis
Kernel Independent Component Analysis
An analysis of the behavior of a class of genetic adaptive systems.
An analysis of the behavior of a class of genetic adaptive systems.
Optimal Linear Representations of Images for Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Cross Entropy Method: A Unified Approach To Combinatorial Optimization, Monte-carlo Simulation (Information Science and Statistics)
Evolutionary computation-based kernel optimal component analysis for pattern recognition
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Representing Images Using Nonorthogonal Haar-Like Bases
IEEE Transactions on Pattern Analysis and Machine Intelligence
Kernel methods and component analysis for pattern recognition
Kernel methods and component analysis for pattern recognition
Tools for application-driven linear dimension reduction
Neurocomputing
Designing and learning of adjustable quasi-triangular norms with applications to neuro-fuzzy systems
IEEE Transactions on Fuzzy Systems
Fast and robust fixed-point algorithms for independent component analysis
IEEE Transactions on Neural Networks
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Component analysis, or basis methods, provide a lower-dimensional representation of a given data set for compression, compaction, or discrimination. Stochastic basis pursuit addresses the problem of finding an optimal basis, either orthogonal or nonorthogonal, for improved pattern discrimination for pattern recognition applications. In this paper, the results of experiments performed with two stochastic optimization techniques as applied to the optimal basis problem are reported. The cost function is a quadratic discriminant function. Testing is done using three publicly available databases and ten-fold cross-validation. Empirical results demonstrate a twelve to fifteen percent average performance improvement over previous results.