Active learning techniques have gained popularity in reducing human effort to annotate data instances for inducing a classifier. When faced with large quantities of unlabeled dat...
Learning problems form an important category of computational tasks that generalizes many of the computations researchers apply to large real-life data sets. We ask: what concept ...
Shiva Prasad Kasiviswanathan, Homin K. Lee, Kobbi ...
In this paper, several effective learning algorithms using global image representations are adjusted and introduced to region-based image retrieval (RBIR). First, the query point m...
Feng Jing, Mingjing Li, Lei Zhang, HongJiang Zhang...
We apply a new active learning formulation to the problem of learning medical concepts from unstructured text. The new formulation is based on maximizing the mutual information th...
Abstract. A variant of iterative learning in the limit (cf. [LZ96]) is studied when a learner gets negative examples refuting conjectures containing data in excess of the target la...