Bayesian networks are a powerful probabilistic representation, and their use for classification has received considerable attention. However, they tend to perform poorly when lear...
Recent computer vision approaches are aimed at richer image interpretations that extend the standard recognition of objects in images (e.g., cars) to also recognize object attribu...
William Curran, Travis Moore, Todd Kulesza, Weng-K...
Local Coordinate Coding (LCC), introduced in (Yu et al., 2009), is a high dimensional nonlinear learning method that explicitly takes advantage of the geometric structure of the d...
We consider the problem of learning density mixture models for classification. Traditional learning of mixtures for density estimation focuses on models that correctly represent t...
We develop a novel multi-class classification method based on output codes for the problem of classifying a sequence of amino acids into one of many known protein structural class...
Eugene Ie, Jason Weston, William Stafford Noble, C...