Dimensionally Reduced Open-World Clustering: DROWCULA

Erencem Ozbey, Dimitrios I. Diochnos

Abstract: Working with annotated data is the cornerstone of supervised learning. Nevertheless, providing labels to instances is a task that requires significant human effort. Several critical real-world applications make things more complicated because no matter how many labels may have been identified in a task of interest, it could be the case that examples corresponding to novel classes may appear in the future. Not unsurprisingly, prior work in this so-called ‘open-world’ context has focused a lot on semi-supervised approaches.

External IDs:doi:10.1007/978-981-95-4969-6_29