Convergence of Gaussian kernelized graph Laplacian: eigen-convergence and bi-stochastic normalization Consider kernelized graph affinity matrix constructed from $N$ data points i.i.d. sampled from a general unknown $d$-dimensional manifold embedded in a possibly high-dimensional space. The setting is generic in graph-based … Read more