The age at which we teach different topics change. If it turns out that students do not learn, say, reading by the time they should, a natural idea is to start teaching them earlie...
We consider learning models for object recognition from examples. Our method is motivated by systems that use the Hausdorff distance as a shape comparison measure. Typically an ob...
Data association (obtaining correspondences) is a ubiquitous problem in computer vision. It appears when matching image features across multiple images, matching image features to ...
This paper investigates a new learning formulation called structured sparsity, which is a naturalextensionofthestandardsparsityconceptinstatisticallearningandcompressivesensing. B...
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. Learning ML...