We propose the so-called Support Feature Machine (SFM) as a novel approach to feature selection for classification, based on minimisation of the zero norm of a separating hyperplan...
In the paper a new measure of distance between events/observations in the pattern space is proposed and experimentally evaluated with the use of k-NN classifier in the context of b...
A new objective function for neural net classifier design is presented, which has more free parameters than the classical objective function. An iterative minimization technique f...
Jiang Li, Michael T. Manry, Li-min Liu, Changhua Y...
Parallel perceptrons (PPs), a novel approach to committee machine training requiring minimal communication between outputs and hidden units, allows the construction of efficient an...
We introduce and discuss the application of statistical physics concepts in the context of on-line machine learning processes. The consideration of typical properties of very large...