A learning problem that has only recently gained attention in the machine learning community is that of learning a classifier from group probabilities. It is a learning task that ...
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
In the past years, the theory and practice of machine learning and data mining have been focused on static and finite data sets from where learning algorithms generate a static m...
The problem of transfer learning, where information gained in one learning task is used to improve performance in another related task, is an important new area of research. While...
We present a mining system that can predict the future health status of the patient using the temporal trajectories of health status of a set of similar patients. The main noveltie...