In this paper we present a novel strategy, DragPushing, for improving the performance of text classifiers. The strategy is generic and takes advantage of training errors to succes...
Songbo Tan, Xueqi Cheng, Moustafa Ghanem, Bin Wang...
As opposed to traditional supervised learning, multiple-instance learning concerns the problem of classifying a bag of instances, given bags that are labeled by a teacher as being...
We introduce confidence-weighted linear classifiers, which add parameter confidence information to linear classifiers. Online learners in this setting update both classifier param...
This paper presents a novel Automatic Question Generation (AQG) approach that generates trigger questions as a form of support for students’ learning through writing. The approac...
Abstract. Question answering systems aim to meet users' information needs by returning exact answers in response to a question. Traditional open domain question answering syst...