In this paper, we investigate a new machine learning framework called Online Transfer Learning (OTL) that aims to transfer knowledge from some source domain to an online learning ...
Abstract. Recent times have seen an explosive growth in the availability of various kinds of data. It has resulted in an unprecedented opportunity to develop automated data-driven ...
Abstract. Model selection is an important problem in statistics, machine learning, and data mining. In this paper, we investigate the problem of enabling multiple parties to perfor...
The standard model of supervised learning assumes that training and test data are drawn from the same underlying distribution. This paper explores an application in which a second...
Aim of this work is to apply a novel comprehensive machine learning tool for data mining to preprocessing and interpretation of gene expression data. Furthermore, some visualizatio...
Roberto Amato, Angelo Ciaramella, N. Deniskina, Ca...