Linear-time Learning on Distributions with Approximate Kernel Embeddings

24 Sep 2015Dougal J. SutherlandJunier B. OlivaBarnabás PóczosJeff Schneider

Many interesting machine learning problems are best posed by considering instances that are distributions, or sample sets drawn from distributions. Previous work devoted to machine learning tasks with distributional inputs has done so through pairwise kernel evaluations between pdfs (or sample sets)... (read more)

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