Classification of real-world data poses a number of challenging problems. Mismatch between classifier models and true data distributions on one hand and the use of approximate inf...
Abstracts "Mixtures at the Interface" David Scott, Rice University Mixture modeling provides an effective framework for complex, high-dimensional data. The potential of m...
Research into design rationale in the past has focused on argumentation-based design deliberations. These approaches cannot be used to support change impact analysis effectively ...
In this paper, we develop algorithms for robust linear regression by leveraging the connection between the problems of robust regression and sparse signal recovery. We explicitly ...
Bayesian analysis is a popular subspace based face recognition method. It casts the face recognition task into a binary classification problem with each of the two classes, intrap...