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47. X i=1 log m d (0) i ,θ∞,t = H (P (d)) + KL(P(d)|| m(d,θ∞,t)) = H (P0) + KL(P0||Pt) Since both H (P0) and KL(P0||Pt) are non-negative functions of distributions [Kullback and Leibler (1951),Shannon (1948)], we conclude that the loss value is higher than H (P0). Therefore, a bounded size dataset should reach the loss value H (P0) + KL(P0||Pt). Formalizing this argument, we define a neighborhood around H(P0) with the size δ > 0 and prove that with probability (1 − ), any dataset of bounded size reaches a value in the neighborhood.
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