Bayesian approaches to supervised learning use priors on the classifier parameters. However, few priors aim at achieving "sparse" classifiers, where irrelevant/redundant...
A new scheme of learning similarity measure is proposed for content-based image retrieval (CBIR). It learns a boundary that separates the images in the database into two parts. Im...
Guodong Guo, Anil K. Jain, Wei-Ying Ma, HongJiang ...
A linear programming technique is introduced that jointly performs feature selection and classifier training so that a subset of features is optimally selected together with the c...
We introduce a new classification algorithm based on the concept of Symmetric Maximized Minimal distance in Subspace (SMMS). Given the training data of authentic samples and impos...
Object recognition systems aiming to work in real world settings should use multiple cues in order to achieve robustness. We present a new cue integration scheme which extends the...