cs763/website/docs/org.md

Lectures will be loosely organized around four **modules**: differential
privacy, applied cryptography, language-based security, and adversarial machine
learning. I will give most of the lectures for the first module (differential
privacy). For the other modules, I will give an overview lecture surveying the
topic and background material. Then, each student will lead one lecture,
presenting a paper and guiding the discussion.  

This is a graduate seminar, so not all lectures are set in stone and there is
considerable flexibility in the material. If you are interested in something not
covered in the syllabus, please let me know!

## Readings and Homework

**Paper discussions** are a core component of this course. You are expected to
read papers before lecture, attend lectures, and participate in discussions.
Before every paper presentation, students are expected to read the paper closely
and understand its significance, including (a) the main problem addressed by the
paper, (b) the primary contributions of the paper, and (c) how the authors solve
the problem in some technical detail.  

The topics we will be reading and thinking about are from the recent research
literature---peer-reviewed and published, but not always completely refined.
Most research papers focus on a very narrow topic and are written for a very
specific technical audience. It also doesn't help that computer science
researchers are generally not the clearest writers, though there are certainly
exceptions. These
[notes](https://web.stanford.edu/class/ee384m/Handouts/HowtoReadPaper.pdf) by
Srinivasan Keshav may help you get more out of reading papers.

To help you prepare for the class discussions, I will also send out a few
questions at least 24 hours before every paper presentation. **Before** each
lecture, you should send me brief answers---a short email is fine, no more than
a few sentences per question. These questions will help you check that you have
understood the papers---they are not meant to be very difficult or
time-consuming and they will not be graded in detail.

## Course Project

The other main component is the **course project**. You will work individually
or in pairs on a topic of your choice, producing a conference-style write-up and
presenting the project at the end of the semester. Successful projects may have
the potential to turn into an eventual research paper or survey. Details can be
found [here](projects/details.md).

## Grading and Evaluation

Grades will be assigned as follows:

- **Discussions: 15%** (Pre-lecture questions and class participation)
- **Paper presentation: 25%**
- **Final project: 60%** (First and second milestones, and final writeup)

## Learning Outcomes

By the end of this course, you should be able to...

- Summarize the basic concepts in differential privacy, applied cryptography,
  language-based security, and adversarial machine learning.
- Use standard techniques from differential privacy to design privacy-preserving
  data analyses.
- Grasp the high-level concepts from research literature on the main course
  topics.
- Present and lead a discussion on recent research results.
- Carry out an in-depth exploration of one topic in the form of a self-directed
  research project.

## Credit Information

This is a **3-credit** graduate seminar. We will meet for two 75-minute class
periods each week over the fall semester, and you should expect to work on
course learning activities for about 3 hours out of classroom for every class
period.

## Academic Integrity

The final project may be done individually or in groups of two students.
Collaborative projects with people outside the class may be allowed, but please
check with me first.

## Access and Accommodation

The University of Wisconsin-Madison supports the right of all enrolled students
to a full and equal educational opportunity. The Americans with Disabilities Act
(ADA), Wisconsin State Statute (36.12), and UW-Madison policy (Faculty Document
1071) require that students with disabilities be reasonably accommodated in
instruction and campus life. Reasonable accommodations for students with
disabilities is a shared faculty and student responsibility. Students are
expected to inform me of their need for instructional accommodations by the end
of the third week of the semester, or as soon as possible after a disability has
been incurred or recognized. I will work either directly with you or in
coordination with the McBurney Center to identify and provide reasonable
instructional accommodations. Disability information, including instructional
accommodations as part of a student’s educational record, is confidential and
protected under FERPA.