Subspace learning based face recognition methods have attracted considerable interests in recent years, including Principal Component Analysis (PCA), Linear Discriminant Analysis ...
Ideally pattern recognition machines provide constant output when the inputs are transformed under a group G of desired invariances. These invariances can be achieved by enhancing...
Sparsity-promoting L1-regularization has recently been succesfully used to learn the structure of undirected graphical models. In this paper, we apply this technique to learn the ...
Mark W. Schmidt, Alexandru Niculescu-Mizil, Kevin ...
We consider the problem of labeling a partially labeled graph. This setting may arise in a number of situations from survey sampling to information retrieval to pattern recognition...
We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...