ruby/tensorflow_privacy
1
0
Fork 0
forked from 626_privacy/tensorflow_privacy
Code Pull requests Activity

last typo

Browse source
This commit is contained in:
npapernot 2019-07-31 20:40:30 +00:00
parent 4bd0ad482a
commit 12dc0b9497
1 changed files with 1 additions and 1 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

2
privacy/bolt_on/README.md
View file

@ -12,7 +12,7 @@ This method uses 4 key steps to achieve privacy guarantees:
2. Projects weights to R, the radius of the hypothesis space,
after each batch. This value is configurable by the user.
3. Limits learning rate
4. Use a strongly convex loss function (see compile)
4. Uses a strongly convex loss function (see compile)
For more details on the strong convexity requirements, see:
Bolt-on Differential Privacy for Scalable Stochastic Gradient