Artificial neural networks (ANNs) have been successfully applied to solve a variety of classification and function approximation problems. Although ANNs can generally predict bett...
Randomly connected recurrent neural circuits have proven to be very powerful models for online computations when a trained memoryless readout function is appended. Such Reservoir ...
Benjamin Schrauwen, Lars Buesing, Robert A. Legens...
This paper introduces an augmentation hybrid system, referred to as Rated MCRDR. It uses Multiple Classification Ripple Down Rules (MCRDR), a simple and effective knowledge acquisi...
This paper presents a novel method for the classification of images that combines information extracted from the images and contextual information. The main hypothesis is that con...
Deep autoencoder networks have successfully been applied in unsupervised dimension reduction. The autoencoder has a "bottleneck" middle layer of only a few hidden units, ...