We show how variational Bayesian inference can be implemented for very large generalized linear models. Our relaxation is proven to be a convex problem for any log-concave model. ...
Locally adaptive classifiers are usually superior to the use of a single global classifier. However, there are two major problems in designing locally adaptive classifiers. First,...
Juan Dai, Shuicheng Yan, Xiaoou Tang, James T. Kwo...
Many data mining techniques are these days in use for ontology learning – text mining, Web mining, graph mining, link analysis, relational data mining, and so on. In the current ...
—This paper presents a semiautomatic framework that aims to produce domain concept maps from text and then to derive domain ontologies from these concept maps. This methodology p...
Abstract. Recent cognitive modeling studies suggest the effectiveness of metaheuristic optimization in describing human cognitive behaviors. Such models are built on the basis of p...