In this paper, we study the problem of learning in the presence of classification noise in the probabilistic learning model of Valiant and its variants. In order to identify the cl...
This paper provides an intelligent multiagent approach to incorporate human temperaments into the filtering process of an information recommendation service. Our approach is to de...
Models of language learning play a central role in a wide range of applications: from psycholinguistic theories of how people acquire new word knowledge, to information systems th...
Latest results of statistical learning theory have provided techniques such us pattern analysis and relational learning, which help in modeling system behavior, e.g. the semantics ...
In the feature selection of cancer classification problems, many existing methods consider genes individually by choosing the top genes which have the most significant signal-to...