This paper presents a method for learning a semantic parser from ambiguous supervision. Training data consists of natural language sentences annotated with multiple potential mean...
Current semi-supervised incremental learning approaches select unlabeled examples with predicted high confidence for model re-training. We show that for many applications this dat...
Rules have been showed to be appropriate representations to model tutoring and can be easily applied to intelligent tutoring systems. We applied a machine learning technique, Class...
In this paper, we propose a multi-criteriabased active learning approach and effectively apply it to named entity recognition. Active learning targets to minimize the human annota...
Dan Shen, Jie Zhang, Jian Su, Guodong Zhou, Chew L...
Surveillance systems that operate continuously generate large volumes of data. One such system is described here, continuously tracking and storing observations taken from multiple...