Tweak links.

website/docs/schedule/lectures.md

@@ -4,8 +4,8 @@
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       | <center> <h4> **Differential Privacy** </h4> </center> | | |
 9/4   | Course welcome <br> **Reading:** [*How to Read a Paper*](https://web.stanford.edu/class/ee384m/Handouts/HowtoReadPaper.pdf) | JH | - |
-9/6   | Basic private mechanisms <br> **Reading:** AFDP 3.2-4 | JH | - |
-9/9   | Composition and closure properties <br> **Reading:** AFDP 3.5 | JH | - | [Paper Signups](https://docs.google.com/spreadsheets/d/1hSbRy0mo3PjlozN0Ph1JkP5JwlRG8y7ukuCdorofncA/edit?usp=sharing)
+9/6   | Basic private mechanisms <br> **Reading:** [AFDP](https://www.cis.upenn.edu/~aaroth/Papers/privacybook.pdf) 3.2-4 | JH | - |
+9/9   | Composition and closure properties <br> **Reading:** [AFDP](https://www.cis.upenn.edu/~aaroth/Papers/privacybook.pdf) 3.5 | JH | - | [Signups](https://docs.google.com/spreadsheets/d/1hSbRy0mo3PjlozN0Ph1JkP5JwlRG8y7ukuCdorofncA/edit?usp=sharing) Due
 9/11  | What does differential privacy actually mean? <br> **Reading:** [Lunchtime for Differential Privacy](https://github.com/frankmcsherry/blog/blob/master/posts/2016-08-16.md) | JH | - |
 9/13  | Differentially private machine learning <br> **Reading:** [*On the Protection of Private Information in Machine Learning Systems: Two Recent Approaches*](https://arxiv.org/pdf/1708.08022) <br> **Reading:** [*Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data*](https://arxiv.org/pdf/1610.05755) | | |
       | <center> <h4> **Adversarial Machine Learning** </h4> </center> | |