From ac8979f6770d2c1ed79b680fc720cbefd8d588c7 Mon Sep 17 00:00:00 2001 From: Yuchen Pei Date: Tue, 19 Mar 2019 16:20:14 +0100 Subject: minor --- posts/2019-03-13-a-tail-of-two-densities.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) 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 460364a..f3e409c 100644 --- a/posts/2019-03-13-a-tail-of-two-densities.md +++ b/posts/2019-03-13-a-tail-of-two-densities.md @@ -8,7 +8,7 @@ comments: true This is Part 1 of a two-part post where I give an introduction to differential privacy, which is a study of tail bounds of the divergence between probability measures, with the end goal of applying it to stochastic -gradient descent. +gradient descent. I start with the definition of $\epsilon$-differential privacy (corresponding to max divergence), followed by -- cgit v1.2.3