Sep 21, 2020 · Abstract:In this paper, we propose a one-stage online clustering method called Contrastive Clustering (CC) which explicitly performs the ...
An extension of this work has been released on https://github.com/Yunfan-Li/Twin-Contrastive-Learning. It significantly improves the clustering performance and ...
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In this paper, we propose an online clustering method called. Contrastive Clustering (CC) which explicitly performs the instance- and cluster-level contrastive ...
(a) Existing contrastive learning based clustering methods mainly focus on instance- level consistency, which maximizes the correlation between self- augmented ...
Nov 14, 2022 · Abstract:Clustering is the task of gathering similar data samples into clusters without using any predefined labels.
In this paper, we extend the mainstream contrastive learning paradigm to a cluster-level scheme, where all the data subjected to the same cluster contribute to.
An online clustering method called Contrastive Clustering (CC) which explicitly performs the instance- and cluster-level contrastive learning and jointly ...
We propose Contrastive Clustering with Effective Sample pairs construction (CCES). •. CCES constructs sample pairs via the nearest neighbor in contrastive ...
Jun 18, 2024 · FedMCC clusters a set of data points distributed over multiple clients and is trained by contrastive loss on a momentum network. Our method can ...
Nov 15, 2023 · Abstract: In this article, a new unsupervised contrastive clustering (CC) model is introduced, namely, image CC with self-learning pairwise ...