44 citations · 56 across the 4 of their papers we have counts for
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Random projection tree similarity metric for SpectralNet
Mashaan Alshammari, John Stavrakakis, Adel F. Ahmed +1
SpectralNet is a graph clustering method that uses neural network to find an embedding that separates the data. So far it was only used with -nn graphs, which are usually constr…
A parameter-free graph reduction for spectral clustering and SpectralNet
Mashaan Alshammari, John Stavrakakis, Masahiro Takatsuka
Graph-based clustering methods like spectral clustering and SpectralNet are very efficient in detecting clusters of non-convex shapes. Unlike the popular -means, graph-based clu…
The Effect of Points Dispersion on the -nn Search in Random Projection Forests
Mashaan Alshammari, John Stavrakakis, Adel F. Ahmed +1
Partitioning trees are efficient data structures for -nearest neighbor search. Machine learning libraries commonly use a special type of partitioning trees called d-trees to…
Refining a -nearest neighbor graph for a computationally efficient spectral clustering
Mashaan Alshammari, John Stavrakakis, Masahiro Takatsuka
Spectral clustering became a popular choice for data clustering for its ability of uncovering clusters of different shapes. However, it is not always preferable over other clusteri…