expectation. It is perhaps more clearly expressed in mathematical notation:
E[f(x)]
>_ f(E[x])
Let's take the simplest example I can think of. A simple convex function is
f(x) - x 2.
Now let's assume that x has a binomial distribution with equally
likely outcomes of 0 and 2. We can now check Jensen's inequality
E[f(x)] -
0.5 • (x - 0) 2 + 0.5 • (x - 2) 2
-2
and the right-hand side of the inequality is given by
f(E[x]) - f(1)
-1
So the inequality held for this case. Another way of understanding the
inequality more generally is via a second-order Taylor ...
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