147 citations · 354 across the 17 of their papers we have counts for
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stat.ML2019★ 82 cited
Deep Divergence-Based Approach to Clustering
Michael Kampffmeyer, Sigurd Løkse, Filippo M. Bianchi +3
A promising direction in deep learning research consists in learning representations and simultaneously discovering cluster structure in unlabeled data by optimizing a discriminati…
stat.ML2017★ 3 cited
Spectral Clustering using PCKID - A Probabilistic Cluster Kernel for Incomplete Data
Sigurd Løkse, Filippo Maria Bianchi, Arnt-Børre Salberg +1
In this paper, we propose PCKID, a novel, robust, kernel function for spectral clustering, specifically designed to handle incomplete data. By combining posterior distributions of…