The increasing volume of data stored as XML documents makes fragmentation techniques an alternative to the performance issues in query processing. Fragmented databases are feasible...
Guilherme Figueiredo, Vanessa P. Braganholo, Marta...
Principal component analysis (PCA) is a classical data analysis technique that finds linear transformations of data that retain the maximal amount of variance. We study a case whe...
We study the problem of image denoising where images are assumed to be samples from low dimensional (sub)manifolds. We propose the algorithm of locally linear denoising. The algor...
We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of t...
Bioabsorbable drug-eluting coronary stents present a very promising improvement to the common metallic ones solving some of the most important problems of stent implantation: the l...