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authorYuchen Pei <me@ypei.me>2019-03-17 09:14:45 +0100
committerYuchen Pei <me@ypei.me>2019-03-17 09:14:45 +0100
commitef11d59204d46388048ada5cd1cc5f850c960549 (patch)
tree43d72d9098e3cea4a31a5cb26d84e7a06cb7a492
parent222df0225755023cc596556f5310ca164e9553ee (diff)
minor
-rw-r--r--posts/2019-03-13-a-tail-of-two-densities.md4
1 files 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 f7d6c91..533835d 100644
--- a/posts/2019-03-13-a-tail-of-two-densities.md
+++ b/posts/2019-03-13-a-tail-of-two-densities.md
@@ -26,7 +26,7 @@ as well as the effect of mixing mechanisms, by presenting the subsampling theore
(a.k.a. amplification theorem).
In [Part 2](/posts/2019-03-14-great-but-manageable-expectations.html), I discuss the Rényi differential privacy, corresponding to
-the Rényi divergence, a study of the moment generating functions the
+the Rényi divergence, a study of the moment generating functions of the
divergence between probability measures to derive the tail bounds.
Like in Part 1, I prove a composition theorem and a subsampling theorem.
@@ -591,7 +591,7 @@ Legendre transformation). When $\xi$ is standard normal, we get (6.5).
$\square$
**Remark**. We will use the Chernoff bound extensively in the
-second part of this post when considering Renyi differential privacy.
+second part of this post when considering Rényi differential privacy.
**Claim 9**. The Gaussian mechanism on a query $f$ is
$(\epsilon, \delta)$-dp, where