Semi-supervised learning aims at taking advantage of unlabeled data to improve the efficiency of supervised learning procedures. For discriminative models however, this is a chall...
Recommender systems are important to help users select relevant and personalised information over massive amounts of data available. We propose an unified framework called Prefer...
We propose a new clustering algorithm, called SyMP, which is based on synchronization of pulse-coupled oscillators. SyMP represents each data point by an Integrate-and-Fire oscill...
Abstract. Graph transformation has a well-established theory and associated tools that can be used to perform model transformations. However, the lack of a construct to match and t...
In this paper, we propose a new semi-supervised training method for Gaussian Mixture Models. We add a conditional entropy minimizer to the maximum mutual information criteria, whi...