High-Dimensional Wide Gap $k$-Means Versus Clustering Axioms

Kleinberg's axioms for distance based clustering proved to be contradictory. Various efforts have been made to overcome this problem. Here we make an attempt to handle the issue by embedding in high-dimensional space and granting wide gaps between clusters.

cs.LG stat.ML Face and Expression Recognition Advanced Clustering Algorithms Research Data Management and Algorithms

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Approximate K-Means via Cluster ClosuresUS 9,710,493 · MICROSOFT CORPORATION · 2017 DENSITY BASED CLUSTERING FOR MULTIDIMENSIONAL DATAUS 9,165,052 · ZYMEWORKS INC. · 2015 CLUSTERING TECHNIQUES FOR LARGE, HIGH-DIMENSIONALITY DATA SETSUS 8,363,961 · ADOBE SYSTEMS INCORPORATED · 2013 Clustering Technique for Optimized Search over High-dimensional SpaceUS 9,864,930 · INTERNATIONAL BUSINESS MACHINES CORPORATION · 2018 FEATURE WEIGHTING IN K-MEANS CLUSTERINGUS 6,952,700 · INTERNATIONAL BUSINESS MACHINES CORPORATION · 2005

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