The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building large-scale multivariate stat...
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...
This paper presents a novel dimension reduction algorithm for kernel based classification. In the feature space, the proposed algorithm maximizes the ratio of the squared between-c...
Senjian An, Wanquan Liu, Svetha Venkatesh, Ronny T...
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 ...
In this paper, we propose a technique based on genetic programming (GP) for meshfree solution of elliptic partial differential equations. We employ the least-squares collocation pr...