Research map / Graph learning / Graph algorithms and clustering
Out-of-sample extension of graph adjacency spectral embedding
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use LLS OOS instead of recomputing the full-graph ASE | Adjacency spectral embedding on random dot product graphs · Random dot product graph | latent-position estimation error: c n^{-1/2} \log n; O(n^{-1/2} \log n) | No clear effect |
| Use constrained plug-in maximum likelihood instead of recomputing the full-graph ASE | Adjacency spectral embedding on random dot product graphs · Random dot product graph | latent-position estimation error: cn^{-1/2} \log n; O(n^{-1/2} \log n) | No clear effect |
| Use LLS OOS rather than full-graph ASE for many simultaneous out-of-sample vertices | Two-block random dot product graph · OOS vertex classification | classification error | Mixed |
| Increase the number of simultaneous OOS vertices and embed them jointly with the in-sample graph | Full-graph ASE · Two-block random dot product graph | classification error | Helped |
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