Abstract. We consider a generalization of the classical max-cut problem where two objective functions are simultaneously considered. We derive some theorems on the existence and th...
Eric Angel, Evripidis Bampis, Laurent Gourvè...
Backpropagation, similar to most learning algorithms that can form complex decision surfaces, is prone to overfitting. This work presents classification-based objective functions, ...
Transfer learning proves to be effective for leveraging labeled data in the source domain to build an accurate classifier in the target domain. The basic assumption behind transf...
Mingsheng Long, Jianmin Wang 0001, Guiguang Ding, ...
Abstract. We propose a novel method, fMRI-Informed Regional Estimation (FIRE), which utilizes information from fMRI in E/MEG source reconstruction. FIRE takes advantage of the spat...
This paper introduces a function that increases the amount of neutrality (inactive code in Genetic Programming) for the Artificial Ant Problem. The objective of this approach is t...