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Found 4 papers, 1 papers with code
Kernel KMeans clustering splits for end-to-end unsupervised decision trees
Trees are convenient models for obtaining explainable predictions on relatively small datasets.
Generalised Mutual Information: a Framework for Discriminative Clustering
In the last decade, recent successes in deep clustering majorly involved the Mutual Information (MI) as an unsupervised objective for training neural networks with increasing regularisations.
Sparse GEMINI for Joint Discriminative Clustering and Feature Selection
Feature selection in clustering is a hard task which involves simultaneously the discovery of relevant clusters as well as relevant variables with respect to these clusters.
Generalised Mutual Information for Discriminative Clustering
In the last decade, recent successes in deep clustering majorly involved the mutual information (MI) as an unsupervised objective for training neural networks with increasing regularisations.
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