Spectral Graph Clustering
15 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Spectral Graph Clustering
Most implemented papers
Approximate spectral clustering density-based similarity for noisy datasets
Also, CONN could be tricked by noisy density between clusters.
Approximate spectral clustering with eigenvector selection and self-tuned $k$
The recently emerged spectral clustering surpasses conventional clustering methods by detecting clusters of any shape without the convexity assumption.
Refining a $k$-nearest neighbor graph for a computationally efficient spectral clustering
mashaan14/Spectral-Clustering
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We proposed a refined version of $k$-nearest neighbor graph, in which we keep data points and aggressively reduce number of edges for computational efficiency.
Random projection tree similarity metric for SpectralNet
mashaan14/RPTree-SpectralNet
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Our experiments revealed that SpectralNet produces better clustering accuracy using rpTree similarity metric compared to $k$-nn graph with a distance metric.
A parameter-free graph reduction for spectral clustering and SpectralNet
mashaan14/SC-parameter-free
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We introduce a graph reduction method that does not require any parameters.
