The complexity of quantitative biomedical models, and the rate at which they are published, is increasing to a point where managing the information has become all but impossible w...
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a linear combination of the input variables while constraining the number of nonze...
Alexandre d'Aspremont, Francis R. Bach, Laurent El...
We introduce a novel workflow that will hopefully open new directions of processing and improvement in image reproduction. Existing gamut mapping algorithms can be classified into ...
A major challenge in frequent-pattern mining is the sheer size of its mining results. To compress the frequent patterns, we propose to cluster frequent patterns with a tightness m...
Boosting is a set of methods for the construction of classifier ensembles. The differential feature of these methods is that they allow to obtain a strong classifier from the comb...