The problem of choosing a good parameter setting for a better generalization performance in a learning task is the so-called model selection. A nested uniform design (UD) methodol...
Chien-Ming Huang, Yuh-Jye Lee, Dennis K. J. Lin, S...
Background: Accurate diagnosis of cancer subtypes remains a challenging problem. Building classifiers based on gene expression data is a promising approach; yet the selection of n...
Background: Recent genomic and bioinformatic advances have motivated the development of numerous network models intending to describe graphs of biological, technological, and soci...
Manuel Middendorf, Etay Ziv, Carter Adams, Jen Hom...
Abstract. In this paper, we elaborate how decision space diversity can be integrated into indicator-based multiobjective search. We introduce DIOP, the diversity integrating multio...
Automated analysis of human affective behavior has attracted increasing attention in recent years. With the research shift toward spontaneous behavior, many challenges have come to...