Finding good representations of text documents is crucial in information retrieval and classification systems. Today the most popular document representation is based on a vector ...
We consider the problem of learning a Riemannian metric associated with a given differentiable manifold and a set of points. Our approach to the problem involves choosing a metric...
Background: Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mecha...
This paper presents a novel method for acquiring a set of query patterns to retrieve documents containing important information about an entity. Given an existing Wikipedia catego...
Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...