SCCL
Supporting Clustering with Contrastive Learning
**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.
Supporting Clustering with Contrastive Learning
https://paperswithcode.com/paper/supporting-clustering-with-contrastive
Supporting Clustering with Contrastive Learning