To bridge the gap between high level semantic concepts and low level visual features in content-based image retrieval (CBIR), online feature selection is really required. An effec...
We present an information theoretic approach for learning a linear dimension reduction transform for object classification. The theoretic guidance of the approach is that the trans...
Instant messaging platforms facilitate coordination in workgroups by providing users with mutual information on their presence and availability, allowing for ad-hoc conversations ...
This paper is a comparative study of feature selection methods in statistical learning of text categorization. The focus is on aggressive dimensionality reduction. Five methods we...
Instance selection and feature selection are two orthogonal methods for reducing the amount and complexity of data. Feature selection aims at the reduction of redundant features i...