Efficient large scale commute time embedding
نویسنده
چکیده
Commute time embedding involves computing eigenfunctions of the graph Laplacian matrix. Spectral decomposition requires computational burden proportional to 3 ( ) O n , which may not be suitable for large scale dataset. This paper proposes computationally efficient commute time embedding by applying Nyström method to the normalized graph Laplacian. The performance of the proposed algorithms is analysed by checking the embedding results on a patch graph.
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