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Softmax-based Classification is k-means Clustering: Formal Proof, Consequences for Adversarial Attacks, and Improvement through Centroid Based Tailoring
We formally prove the connection between k-means clustering and the pred...
01/07/2020 ∙ by Sibylle Hess, et al. ∙
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k is the Magic Number -- Inferring the Number of Clusters Through Nonparametric Concentration Inequalities
Most convex and nonconvex clustering algorithms come with one crucial pa...
07/04/2019 ∙ by Sibylle Hess, et al. ∙
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The Trustworthy Pal: Controlling the False Discovery Rate in Boolean Matrix Factorization
Boolean matrix factorization (BMF) is a popular and powerful technique f...
07/01/2019 ∙ by Sibylle Hess, et al. ∙
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The SpectACl of Nonconvex Clustering: A Spectral Approach to Density-Based Clustering
When it comes to clustering nonconvex shapes, two paradigms are used to ...
07/01/2019 ∙ by Sibylle Hess, et al. ∙
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The PRIMPing Routine -- Tiling through Proximal Alternating Linearized Minimization
Mining and exploring databases should provide users with knowledge and n...
06/17/2019 ∙ by Sibylle Hess, et al. ∙
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