— We propose the Multiresponse Sparse Regression algorithm, an input selection method for the purpose of estimating several response variables. It is a forward selection procedur...
A relevance filter is proposed which removes features based on the mutual information between class labels and features. It is proven that both feature independence and class condi...
Abstract - We discuss an ensemble-of-classifiers based algorithm for the missing feature problem. The proposed approach is inspired in part by the random subspace method, and in pa...
Based on rank-1 update, Sparse Bayesian Learning Algorithm (SBLA) is proposed. SBLA has the advantages of low complexity and high sparseness, being very suitable for large scale pr...