The principle of maximizing mutual information is applied to learning overcomplete and recurrent representations. The underlying model consists of a network of input units driving...
Prior knowledge, in the form of simple advice rules, can greatly speed up convergence in learning algorithms. Online learning methods predict the label of the current point and the...
Gautam Kunapuli, Kristin P. Bennett, Amina Shabbee...
— To enhance the generalization capacity of a distribution learning method, we propose to use a fuzzy Bayesian framework based on Bayes rules. The precision of the learning resul...
Association Rule Mining algorithms operate on a data matrix to derive association rule, discarding the quantities of the items, which contains valuable information. In order to mak...
For unsupervised clustering in a network of spiking neurons we develop a temporal encoding of continuously valued data to obtain arbitrary clustering capacity and precision with a...