Prepare signup sheets.
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## Five modules
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1. Differential privacy
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2. Adversarial machine learning
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3. Applied cryptography
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3. Crytpography in machine learning
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4. Algorithmic fairness
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5. PL and verification
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- Messing with training data
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- Extracting training information
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# Applied crypto
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# Cryptography in machine learning
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##
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- In groups of three (or very rarely two)
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- See website for [project details](https://pages.cs.wisc.edu/~justhsu/teaching/current/cs763/assignments/project/)
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- Key dates:
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- **September 9**: Form groups, pick topic
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- **October 11**: Milestone 1
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- **November 8**: Milestone 2
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- **End of class**: Final writeups and presentations
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## Todos for you
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0. Complete the [course survey](https://forms.gle/NvYx3BM7HVkuzYdG6)
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1. Explore the [course website](https://pages.cs.wisc.edu/~justhsu/teaching/current/cs763/)
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2. Think about which lecture you want to present
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2. Think about which lecture you want to present and summarize
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3. Think about which lecture you want to summarize
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4. Brainstorm project topics
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4. Form project groups and brainstorm topics
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> Signup for slots and projects [here](https://docs.google.com/spreadsheets/d/1hSbRy0mo3PjlozN0Ph1JkP5JwlRG8y7ukuCdorofncA/edit?usp=sharing)
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## We will move quickly
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- First deadline: **next Monday, September 9**
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- Form paper and project groups
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- Signup sheet [here](https://docs.google.com/spreadsheets/d/1hSbRy0mo3PjlozN0Ph1JkP5JwlRG8y7ukuCdorofncA/edit?usp=sharing)
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- Please: don't sign up for the same slot
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- First slot is soon: **next Friday, September 13**
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- Only slot for presenting differential privacy
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- I will help the first group prepare
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# Defining privacy
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The first key date is **September 9**. By this date, you should:
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- **Sign up** with a partner to present and scribe.
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- **Form project groups** of three.
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- **Brainstorm** project topics. Try to come up with **1-2 sentences**
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describing your initial direction. This is not a firm commitment---you can
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change your topic as you learn more.
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- **Form project groups** of three and **brainstorm** project topics. Try to
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come up with **1-2 sentences** describing your initial direction. This is not
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a firm commitment---you can change your topic as you learn more.
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The signup sheet is [here](https://docs.google.com/spreadsheets/d/1hSbRy0mo3PjlozN0Ph1JkP5JwlRG8y7ukuCdorofncA/edit?usp=sharing).
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## Project Deadlines
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- Milestone 1: **October 11**
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| <center> <h4> **Differential Privacy** </h4> </center> | | |
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9/4 | Course welcome <br> **Reading:** [*How to Read a Paper*](https://web.stanford.edu/class/ee384m/Handouts/HowtoReadPaper.pdf) | JH | - |
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9/6 | Basic private mechanisms <br> **Reading:** AFDP 3.2-4 | JH | - |
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9/9 | Composition and closure properties <br> **Reading:** AFDP 3.5 | JH | - | Paper Signups
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9/9 | Composition and closure properties <br> **Reading:** AFDP 3.5 | JH | - | [Paper Signups](https://docs.google.com/spreadsheets/d/1hSbRy0mo3PjlozN0Ph1JkP5JwlRG8y7ukuCdorofncA/edit?usp=sharing)
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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 | - |
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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) | | |
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| <center> <h4> **Adversarial Machine Learning** </h4> </center> | |
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