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Found 2 papers, 1 papers with code
Clustering-friendly Representation Learning via Instance Discrimination and Feature Decorrelation
In this paper, we propose a clustering-friendly representation learning method using instance discrimination and feature decorrelation.
Ranked #6 on
Image Clustering
on ImageNet-10
RDEC: Integrating Regularization into Deep Embedded Clustering for Imbalanced Datasets
DEC optimizes cluster assignments by pushing data more densely around centroids in latent space, but it is sometimes sensitive to the initial location of centroids, especially in the case of imbalanced data, where the minor class has less chance to be assigned a good centroid.
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