Hi everybody. While reviewing the label propagation PR, I thought about the pairwise rbf functions. Would it be possible to compute an sparse, approximate RBF kernel matrix using ball trees? The idea would be that if the distance between two points is some "large" multiple of gamma, the kernel can be assumed to be zero. Do you think this is feasible to implement and helpful for real data?
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