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, ...
Multi-label learning is useful in visual object recognition when several objects are present in an image. Conventional approaches implement multi-label learning as a set of binary...
Multilabel classification is a challenging research problem in which each instance is assigned to a subset of labels. Recently, a considerable amount of research has been concerned...
Muhammad Atif Tahir, Josef Kittler, Krystian Mikol...
Abstract: Multi-label learning originated from the investigation of text categorization problem, where each document may belong to several predefined topics simultaneously. In mul...