There are many situations in which we have more than one view of a single data source, or in which we have multiple sources of data that are aligned. We would like to be able to bu...
Visual attributes expose human-defined semantics to object recognition models, but existing work largely restricts their influence to mid-level cues during classifier training....
Radial symmetry is an important perceptual cue for the feature-based representation, fixation, and description of large-scale data sets. A new approach based on iterative voting a...
One of the nice properties of kernel classifiers such as SVMs is that they often produce sparse solutions. However, the decision functions of these classifiers cannot always be u...
We propose a Bayesian undirected graphical model for co-training, or more generally for semi-supervised multi-view learning. This makes explicit the previously unstated assumption...