Question: Given a dataset {x 1 ; x 2 ; : : : ; x n } containing samples drawn from an unknown data distribution p(x),

Given a dataset {x₁; x₂; : : : ; x_{n }}containing samples drawn from an unknown data distribution p(x), we want to learn a distribution p(x) that is as close as possible to the true distribution p(x). Consider two cost functions to find the optimal p(x): D_K_L(p(x)I p(x)) and x (p(x) p(x))²dx. Choose the best cost function out of these.

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