Abstract. This paper proposes a generic extension to propositional rule learners to handle multiple-instance data. In a multiple-instance representation, each learning example is r...
Multiple-instance learning (MIL) is a generalization of the supervised learning problem where each training observation is a labeled bag of unlabeled instances. Several supervised ...
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
Background: Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles...
Michael Gormley, William Dampier, Adam Ertel, Bilg...
Human activity recognition has potential to impact a wide range of applications from surveillance to human computer interfaces to content based video retrieval. Recently, the rapi...
Kiwon Yun, Jean Honorio, Debaleena Chattopadhyay, ...