Oct

15

Nicely-done video on Jensen's inequality.

And some interesting reads:

Jensen’s Inequality As An Intuition Tool

Jensen’s Inequality guides our predictions by forcing us to deliberately consider how the average input maps to the average output. When the function that maps the input to the output is non-linear, Jensen’s Inequality tells us in which direction our predictions will be biased. Stated another way: Jensen’s Inequality informs us when an average occurance is a poor predictor of the average result.

Jensen’s Inequality (2): Unlocking Optimization and Decision-Making Power

Jensen’s inequality is a simple yet powerful concept. In short, it states that for a convex function, the function’s value at the average of some points is less than or equal to the average of the function’s values at those points. At first glance, this may seem rather abstract. But its implications are profound. Jensen’s inequality allows us to derive bounds and build intuition about complex systems.


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