Bayesian posterior approximation via greedy particle approximation

This paper is about the approximation method for posterior distribution by the particle optimization method.

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Outline

• We propose new particle approximation based on convex optimization of maximum mean discrepancy (MMD).
• We solve it with the Frank-Wolfe (FW) algorithm.
• We establish a finite sample bound of the convergence rate which is in the linear order.