Recent research has shown that the provisional count of votes of an ensemble of classifiers can be used to estimate the probability that the final ensemble prediction coincides w...
Humans tend to group together related properties in order to understand complex phenomena. When modeling large problems with limited representational resources, it is important to...
This paper examines the computational role of inhibition as it moves towards balancing concurrent excitation using the biologically-inspired Temporal Noisy-Leaky Integrator (TNLI) ...
Chris Christodoulou, Trevor G. Clarkson, John G. T...
Many machine learning algorithms can be formulated as the minimization of a training criterion which involves (1) \training errors" on each training example and (2) some hype...
Abstract: Support vector machines (SVMs) are primarily designed for 2-class classification problems. Although in several papers it is mentioned that the combination of K SVMs can b...