SCCL

2000년 도입 · 논문 4편에서 사용

SCCL, or Supporting Clustering with Contrastive Learning, is a framework to leverage contrastive learning to promote better separation in unsupervised clustering. It combines the top-down clustering with the bottom-up instance-wise contrastive learning to achieve better inter-cluster distance and intra-cluster distance. During training, we jointly optimize a clustering loss over the original data instances and an instance-wise contrastive loss over the associated augmented pairs.

출처: Supporting Clustering with Contrastive Learning

소개 논문: Supporting Clustering with Contrastive Learning