When: May 21, 2013 from 3PM to 4:30PM
Where: room B11
Speaker: Jesse Read
Title: Advances in Multi-label Classification
Abstract: In multi-label classification, each data instance may be associated with multiple classes, as opposed to a single class label. The multi-label context arises naturally in many domains, such as text categorisation and labelling images. The main challenge is modelling dependencies between labels, which must be done efficiently to scale up to settings involving large datasets and data streams. This talk reviews recent advances in multi-label classification specific to the approach of ‘classifier chains’, and also discusses methods for multi-label learning in the context of data streams.