Abstract. For a network of spiking neurons with reasonable postsynaptic potentials, we derive a supervised learning rule akin to traditional error-back-propagation, SpikeProp and s...
Sander M. Bohte, Joost N. Kok, Johannes A. La Pout...
This paper describes a method of supervised learning based on forward selection branching. This method improves fault tolerance by means of combining information related to general...
The fastest learning automata (LA) algorithms currently available fall in the family of estimator algorithms introduced by Thathachar and Sastry [24]. The pioneering work of these ...
Comparative machine learning experiments have become an important methodology in empirical approaches to natural language processing (i) to investigate which machine learning algor...
For quantitative analysis of histopathological images,
such as the lymphoma grading systems, quantification of
features is usually carried out on single cells before categorizing...
Hui Kong, Metin Gurcan, and Kamel Belkacem-Boussai...