The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building large-scale multivariate stat...
Clustering with partial supervision finds its application in situations where data is neither entirely nor accurately labeled. This paper discusses a semisupervised clustering algo...
This paper proposes a novel method for blindly separating unobservable independent component (IC) signals based on the use of a genetic algorithm. It is intended for its applicati...
The purpose of this research is to develop effective machine learning or data mining techniques based on flexible neural tree FNT. Based on the pre-defined instruction/operator se...
A function of a protein is dependent on its structure; therefore, predicting a protein structure from an amino acid sequence is an active area of research. Optimally predicting a ...