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Deep Clustering With Concrete K-Means

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IEEE ICASSP 2020 Virtual Conference May 2020

We address the problem of simultaneously learning a k-means clustering and deep feature representation from unlabelled data, which is of interest due to the potential for deep k-means to outperform traditional two-step feature extraction and shallow clust

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Deep Clustering With Concrete K-Means

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We address the problem of simultaneously learning a k-means clustering and deep feature representation from unlabelled data, which is of interest due to the potential for deep k-means to outperform traditional two-step feature extraction and shallow clust