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logistic regression CRFs can be seen as a generalization of logistic regression. So we will begin by reviewing logistic regression. This is the simplest example of a " log-linear model " where the(More)
If h(x) = |x| then we have P (|X| ≥ a) ≤ E|X| a. This is the classic Markov inequality. Note that without further assumptions, the bound is sharp. In particular, consider the deterministic random(More)
0 |f(s)|ds ≤ |t| ≤ 1. Therefore the image of Bp is (uniformly) bounded. By Arzela-Ascoli, V : L p[0, 1]→ C[0, 1] is compact. The preceeding argument does not go through when V acts on L1[0, 1]. In(More)