Two adaptive kernel selection techniques for Kernelized Diffusion Maps are developed, backed by proofs of Lipschitz dependence on kernel weights, spectral projector continuity under gap conditions, residual control, and exponential consistency of the selector.
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Adaptive Kernel Selection for Kernelized Diffusion Maps
Two adaptive kernel selection techniques for Kernelized Diffusion Maps are developed, backed by proofs of Lipschitz dependence on kernel weights, spectral projector continuity under gap conditions, residual control, and exponential consistency of the selector.