Most approaches to classifying media content assume a fixed, closed vocabulary of labels. In contrast, we advocate machine learning approaches which take advantage of the millions...
The great majority of genetic programming (GP) algorithms that deal with the classification problem follow a supervised approach, i.e., they consider that all fitness cases availab...
Junio de Freitas, Gisele L. Pappa, Altigran Soares...
In this paper, we propose a general framework for sparse semi-supervised learning, which concerns using a small portion of unlabeled data and a few labeled data to represent targe...
Relevance Feedback has proven very effective for improving retrieval accuracy. A difficult yet important problem in all relevance feedback methods is how to optimally balance the...
In this paper we address a method of source separation in the case where sources have certain temporal structures. The key contribution in this paper is to incorporate Gaussian pro...