Abstract. Active learning refers to the task of devising a ranking function that, given a classifier trained from relatively few training examples, ranks a set of additional unlabe...
We consider a special type of multi-label learning where class assignments of training examples are incomplete. As an example, an instance whose true class assignment is (c1, c2, ...
In this paper, we propose an attribute retrieval approach which extracts and ranks attributes from HTML tables. We distinguish between class attribute retrieval and instance attri...
We consider the problem of performing learning and inference in a large scale knowledge base containing imperfect knowledge with incomplete coverage. We show that a soft inference...
To bridge the semantic gap in content-based image retrieval, detecting meaningful visual entities (e.g. faces, sky, foliage, buildings etc) in image content and classifying images...