Sharp finite-sample large deviation bounds for independent variables

We show an extension of Sanov's theorem in large deviations theory, controlling the tail probabilities of i.i.d. random variables with matching concentration and anti-concentration bounds. This result applies to samples of any size, and has a short information-theoretic proof using elementary techniques.