REVIEW 1 cited by
On spectral partitioning of signed graphs
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
Signed reviews
read the original abstract
We argue that the standard graph Laplacian is preferable for spectral partitioning of signed graphs compared to the signed Laplacian. Simple examples demonstrate that partitioning based on signs of components of the leading eigenvectors of the signed Laplacian may be meaningless, in contrast to partitioning based on the Fiedler vector of the standard graph Laplacian for signed graphs. We observe that negative eigenvalues are beneficial for spectral partitioning of signed graphs, making the Fiedler vector easier to compute.
Forward citations
Cited by 1 Pith paper
-
Optimization of geometric hypergraph embedding
Two new spectral algorithms, GDSE and GDE, learn Euclidean embeddings of hypergraphs by optimizing a smoothed reconstruction loss, recovering planted geometry and improving spurious/missing membership detection and cl...
Discussion (0). Continue with ORCID to comment.