Improved convergence rate of kNN graph Laplacians: differentiable self-tuned affinity

ArXi:2410.23212v2 Announce Type: replace-cross In graph-based data analysis, $k$-nearest neighbor ($k$NN) graphs are widely used due to their adaptivity to local data densities. Allowing weighted edges in the graph, the kernelized graph affinity provides a general type of $k$NN graph where the $k$NN distance is used to set the kernel bandwidth adaptively.