This paper addresses the problem of classification in situations where the data distribution is not homogeneous: Data instances might come from different locations or times, and t...
Probabilistic matrix factorization (PMF) is a powerful method for modeling data associated with pairwise relationships, finding use in collaborative filtering, computational biolo...
The process of knowledge discovery from databases is a knowledge intensive, highly user-oriented practice, thus has recently heralded the development of ontology-incorporated data ...
We propose a multivariate statistical framework for regional development assessment based on structural equation modelling with latent variables and show how such methods can be c...
Machine learning research often has a large experimental component. While the experimental methodology employed in machine learning has improved much over the years, repeatability ...