Group-Lasso estimators, useful in many applications, suffer from lack of meaningful variance estimates for regression coefficients. To overcome such problems, we propose a full Ba...
Sudhir Raman, Thomas J. Fuchs, Peter J. Wild, Edga...
— To enhance the generalization capacity of a distribution learning method, we propose to use a fuzzy Bayesian framework based on Bayes rules. The precision of the learning resul...
Video segmentation requires the partitioning of a series of images into groups that are both spatially coherent and smooth along the time axis. We formulate segmentation as a Bayes...
DNA arrays yield a global view of gene expression and can be used to build genetic networks models, in order to study relations between genes. Literature proposes Bayesian network ...
In complex distributed applications, a problem is often decomposed into a set of subproblems that are distributed to multiple agents. We formulate this class of problems with a tw...