From 31f1546d123eb571661f0e7373b7cae0d6b26dad Mon Sep 17 00:00:00 2001
From: Yuchen Pei <me@ypei.me>
Date: Wed, 20 Mar 2019 14:05:04 +0100
Subject: minor

---
 posts/2019-03-13-a-tail-of-two-densities.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/posts/2019-03-13-a-tail-of-two-densities.md b/posts/2019-03-13-a-tail-of-two-densities.md
index 1d9cf75..a7a39cf 100644
--- a/posts/2019-03-13-a-tail-of-two-densities.md
+++ b/posts/2019-03-13-a-tail-of-two-densities.md
@@ -590,14 +590,14 @@ using
 
 $$\int_t^\infty e^{- {y^2 \over 2}} dy < \int_t^\infty {y \over t} e^{- {y^2 \over 2}} dy.$$
 
-The second is shown using Chernoff bound. For any random variable $\xi$,
+The second is shown using [Chernoff bound](https://en.wikipedia.org/wiki/Chernoff_bound). For any random variable $\xi$,
 
 $$\mathbb P(\xi > t) < {\mathbb E \exp(\lambda \xi) \over \exp(\lambda t)} = \exp(\kappa_\xi(\lambda) - \lambda t), \qquad (6.7)$$
 
 where $\kappa_\xi(\lambda) = \log \mathbb E \exp(\lambda \xi)$ is the
 cumulant of $\xi$. Since (6.7) holds for any $\lambda$, we can get the
 best bound by minimising $\kappa_\xi(\lambda) - \lambda t$ (a.k.a. the
-Legendre transformation). When $\xi$ is standard normal, we get (6.5).
+[Legendre transformation](https://en.wikipedia.org/wiki/Legendre_transformation)). When $\xi$ is standard normal, we get (6.5).
 $\square$
 
 **Remark**. We will use the Chernoff bound extensively in the
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