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Research map / Graph learning / Graph algorithms and clustering

Multiple Kernel Clustering with Kernel k-Means Coupled Graph Tensor Learning

AAAI 2021 · Graph learning › Graph algorithms and clustering · approach: Neural and local graph clustering · 76 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Couple KKM-derived candidate affinity graphs with low-rank graph-tensor learning, then cluster the averaged graphMultiple-kernel clustering · BBCSport2ACC: 95.04 -> 99.82Helped
Couple KKM-derived candidate affinity graphs with low-rank graph-tensor learning, then cluster the averaged graphMultiple-kernel clustering · Flower17, Caltech101, Mfeat, UCI-Digit, CCV, Flower102ACCHelped
Couple KKM-derived candidate affinity graphs with low-rank graph-tensor learning, then cluster the averaged graphMultiple-kernel clustering · ProteinFoldACC: 40.49 -> 39.63Hurt
Couple KKM-derived candidate affinity graphs with low-rank graph-tensor learning, then cluster the averaged graphMultiple-kernel clustering · ProteinFoldNMI: 48.96 -> 45.89Hurt
Couple KKM-derived candidate affinity graphs with low-rank graph-tensor learning, then cluster the averaged graphMultiple-kernel clustering · ProteinFoldPurity: 46.85 -> 41.35Hurt
Couple KKM-derived candidate affinity graphs with low-rank graph-tensor learning, then cluster the averaged graphMultiple-kernel clustering · All eight datasetsNMIMixed
Couple KKM-derived candidate affinity graphs with low-rank graph-tensor learning, then cluster the averaged graphMultiple-kernel clustering · All eight datasetsPurityMixed

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