A non-parametric hierarchical Bayesian framework is developed for designing a classifier, based on a mixture of simple (linear) classifiers. Each simple classifier is termed a loc...
Chunping Wang, Xuejun Liao, Lawrence Carin, David ...
Background: Feature selection techniques are critical to the analysis of high dimensional datasets. This is especially true in gene selection from microarray data which are common...
Pengyi Yang, Bing Bing Zhou, Zili Zhang, Albert Y....
In this paper, we present a novel joint sparse representation based method for acoustic signal classification with multiple measurements. The proposed method exploits the correla...
Haichao Zhang, Nasser M. Nasrabadi, Thomas S. Huan...
This paper introduces an approach for identifying predictive structures in relational data using the multiple-instance framework. By a predictive structure, we mean a structure th...
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...