Selective sampling, a form of active learning, reduces the cost of labeling training data by asking only for the labels of the most informative unlabeled examples. We introduce a ...
Deciding whether a graph can be embedded in a grid using only unitlength edges is NP-complete, even when restricted to binary trees. However, it is not difficult to devise a numbe...
Abstract. In many organizations, it is common to control access to confidential information based on the need-to-know principle; The requests for access are authorized only if the ...
This paper addresses the problem of transductive learning of the kernel matrix from a probabilistic perspective. We define the kernel matrix as a Wishart process prior and construc...
Abstract--Recently, the following discrimination aware classification problem was introduced: given a labeled dataset and an attribute , find a classifier with high predictive accu...