This paper presents a method of learning and recognizing generic object categories using part-based spatial models. The models are multiscale, with a scene component that specifie...
We consider the problem of segmenting a webpage into visually and semantically cohesive pieces. Our approach is based on formulating an appropriate optimization problem on weighte...
In automated multi-label text categorization, an automatic categorization system should output a category set, whose size is unknown a priori, for each document under analysis. Ma...
Claudine Badue, Felipe Pedroni, Alberto Ferreira d...
In this paper, we propose a probabilistic framework targeting three important issues in the computation of quality and trust in decentralized systems. Specifically, our approach a...
Several problems in text categorization are too hard to be solved by standard bag-of-words representations. Work in kernel-based learning has approached this problem by (i) consid...