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Found 3 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
Investigating Critical Risk Factors in Liver Cancer Prediction
We exploit liver cancer prediction model using machine learning algorithms based on epidemiological data of over 55 thousand peoples from 2014 to the present.
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.
