Multibiometric systems fuse information from different sources to compensate for the limitations in performance of individual matchers. We propose a framework for optimal combinati...
Karthik Nandakumar, Yi Chen, Sarat C. Dass, Anil K...
When users combine data from multiple sources into a spreadsheet or dataset, the result is often a mishmash of different formats, since phone numbers, dates, course numbers and ot...
Abstract. We propose an algorithm for Sparse Bayesian Classification for multi-class problems using Automatic Relevance Determination(ARD). Unlike other approaches which treat mult...
Supervised learning from multiple labeling sources is an increasingly important problem in machine learning and data mining. This paper develops a probabilistic approach to this p...
Background: Predictive classification on the base of gene expression profiles appeared recently as an attractive strategy for identifying the biological functions of genes. Gene O...