We consider support vector machines for binary classification. As opposed to most approaches we use the number of support vectors (the "L0 norm") as a regularizing term ...
We study the problem of modeling species geographic distributions, a critical problem in conservation biology. We propose the use of maximum-entropy techniques for this problem, s...
We present a method for the simultaneous detection and segmentation of objects from static images. We employ lowlevel contour features that enable us to learn the coarse object sh...
In the last few years, Facial Expression Synthesis (FES) has been a flourishing area of research driven by applications in character animation, computer games, and human computer ...
We present sparse topical coding (STC), a non-probabilistic formulation of topic models for discovering latent representations of large collections of data. Unlike probabilistic t...