A novel method for optimizing spectral rotation embedding \(K\)-means with coordinate descent

DOI10.1016/j.ins.2022.09.011OpenAlexW4296311673MaRDI QIDQ6125254

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Publication date: 11 April 2024

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2022.09.011

zbMATH Keywords

clusteringspectral clustering\(K\)-meanscoordinate descentspectral rotationLloyd's heuristic

Mathematics Subject Classification ID

Mathematical programming (90Cxx) Computer science (68-XX)

Cites Work

• Algorithm AS 136: A K-Means Clustering Algorithm
• Smaller coresets for \(k\)-median and \(k\)-means clustering
• Near-optimal large-scale k-medoids clustering
• Multi-view spectral clustering for uncertain objects
• Improved clustering algorithms for image segmentation based on non-local information and back projection
• Coordinate descent algorithms
• Dimensionality Reduction for k-Means Clustering and Low Rank Approximation
• Turning Big Data Into Tiny Data: Constant-Size Coresets for $k$-Means, PCA, and Projective Clustering
• Least squares quantization in PCM
• Unsupervised Learning of Image Segmentation Based on Differentiable Feature Clustering
• Adaptive density-based clustering algorithm with shared KNN conflict game

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