WebJensen's inequality is a powerful mathematical tool and one of the workhorses in statistical learning. Its applications therein include the EM ... maximum conditional likelihood, large margin discriminative models and conditional Bayesian inference. Convergence, efficiency and prediction results are shown. 1 WebMay 16, 2024 · Relative entropy is a well-known asymmetric and unbounded divergence measure [], whereas the Jensen-Shannon divergence [19,20] (a.k.a. the capacitory discrimination []) is a bounded symmetrization of relative entropy, which does not require the pair of probability measures to have matching supports.It has the pleasing property that …
When Jensen
WebJensen’s Inequality Jensen’s inequality applies to convex functions. Intuitively a function is convex if it is “upward bending”. f(x) = x2 is a convex function. To make this definition precise consider two real numbers x 1 and x 2. f is convex if the line between f(x 1) and f(x 2) stays above the function f. To make this even Webtionals : K!R are given. Moreover, a few applications of the conditional Jensen’s inequality are presented. 2 Preliminary Result. The auxiliary result below is a conditional analogue of the similar statement for the usual expectation in a Banach space. We include it here for future reference, but it may be also of independent interest. euro footwear sizing to us
Jensen
Webtionals : K!R are given. Moreover, a few applications of the conditional Jensen’s inequality are presented. 2 Preliminary Result. The auxiliary result below is a conditional analogue … WebBoole's inequality, Bonferroni inequalities Boole's inequality (or the union bound ) states that for any at most countable collection of events, the probability that at least one of the events happens is no greater than the sum of the probabilities of the events in the collection. WebJensen’s Inequality: Let C Rdbe convex and suppose that X2C. Provided that all expectations are well-defined, the following hold. (1)The expectation EX2C (2)If f: C!R is convex then f(EX) Ef(X). If fis strictly convex and Xis not constant then the inequality is strict. (3)If f: C!R is concave then f(EX) Ef(X). If fis strictly concave and Xis euroforest holdings limited