Combining multiple global models (e.g. back-propagation based neural networks) is an effective technique for improving classification accuracy by reducing a variance through manipu...
: This paper presents a new approach to equalization of communication channels using Artificial Neural Networks (ANNs). A novel method of training the ANNs using Tabu based Back Pr...
Several types of network trafic have been shown to exhibit long-range dependence (LRD). In this work, we show that the busy period of an ATM system driven by a long-range dependen...
Background: Protein topology representations such as residue contact maps are an important intermediate step towards ab initio prediction of protein structure. Although improvemen...
We present context-sensitive Multiple Task Learning, or csMTL as a method of inductive transfer. It uses additional contextual inputs along with other input features when learning ...