Abstract. We propose a novel active learning strategy based on the compression framework of [9] for label ranking functions which, given an input instance, predict a total order ov...
act out the core search problem of active learning schemes, to better understand the extent to which adaptive labeling can improve sample complexity. We give various upper and low...
Active learning methods have been considered with an increasing interest in the content-based image retrieval (CBIR) community. In this article, we propose an efficient method bas...
Active learning is well-suited to many problems in natural language processing, where unlabeled data may be abundant but annotation is slow and expensive. This paper aims to shed ...
Active learning is a framework that has attracted a lot of research interest in the content-based image retrieval (CBIR) in recent years. To be effective, an active learning syste...