243 citations · 694 across the 14 of their papers we have counts for
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cs.LG2020★ 217 cited
Fast and Eager k-Medoids Clustering: O(k) Runtime Improvement of the PAM, CLARA, and CLARANS Algorithms
Erich Schubert, Peter J. Rousseeuw
Clustering non-Euclidean data is difficult, and one of the most used algorithms besides hierarchical clustering is the popular algorithm Partitioning Around Medoids (PAM), also sim…
cs.LG2020★ 6 cited
BETULA: Numerically Stable CF-Trees for BIRCH Clustering
Andreas Lang, Erich Schubert
BIRCH clustering is a widely known approach for clustering, that has influenced much subsequent research and commercial products. The key contribution of BIRCH is the Clustering Fe…
stat.ML2020★ 5 cited
ABID: Angle Based Intrinsic Dimensionality
Erik Thordsen, Erich Schubert
The intrinsic dimensionality refers to the ``true'' dimensionality of the data, as opposed to the dimensionality of the data representation. For example, when attributes are highly…