In this work, we propose a novel approximated collapsed variational Bayes approach to model selection in linear regression. The approximated collapsed variational Bayes algorithm offers improvement…
Finding a small set of representatives from an unlabeled dataset is a core problem in a broad range of applications such as dataset summarization and information extraction. Classical exemplar sele…