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Welcome to CS 763!

!!! attention * Due to COVID-19, CS 763 will be conducted virtually. * All times are Madison local time.

This is a graduate-level course covering advanced topics in security and privacy in data science. The field is eclectic, and so is this course. We will start with three core areas: differential privacy, adversarial machine learning, and applied cryptography in machine learning. Then, we will cover two advanced topic areas; this year, algorithmic fairness and formal verification for data science. This is a project based course: in small groups, students will be expected to complete a final project on a technical topic related to the course.

Besides covering technical material, this course will emphasize research skills: reading research papers, presenting technical material, and writing summaries and reviews.

Logistics

  • Course: CS 763, Fall 2020
  • Time: Monday, Wednesday, Friday, 2:30-3:45
  • Location: BB Collaborate Ultra (BBCU)

For the first ten weeks, lectures will be held on Monday, Wednesday, and Friday. In the remaining five weeks, you will work on your course projects. Though there are no lectures scheduled in this period, I will be available to meet as needed.

Accommodations for Remote Students

To provide opportunities for live discussion, lectures will be held synchronously. To accommodate students attending from other time zones, all lectures will be recorded and uploaded to BBCU (this may take a few hours). Students who are not able to attend synchronously will not be able to present a paper and write a presentation summary. Instead, these students will complete paper reviews asynchronously. See the assignments tab for more information.

Grading

Grades will be posted on Canvas.

  • Presentation and summary

    • Paper presentation: 15%
    • Presentation summary: 15%

  • OR: Paper reviews (remote only)

    • 16 reviews: 30%

  • Course project

    • Milestone 1: 10%
    • Milestone 2: 10%
    • Final project: 50%

Everything except the final project will be graded on a simple scale: no submission, below expectations, meets expectations, or exceeds expectations. The final project will be graded on a 10-point scale.

Academic Honesty

Writing is a central part of this course. All students are expected to follow academic honesty standards. In brief: all the text that you submit must be in your own words, and you are not allowed to copy anything---from a paper, or from someone else---without full attribution.

If you are completing paper reviews, you should not search for reviews that may be online---this is expressly against the course policies. You should complete the review as if you were seeing the paper for the first time.

Piazza

We will be using Piazza to discuss papers, ask questions, and find group members:

You can also contact me directly. To ensure that your email goes to the right place, please start the subject with CS763.

HotCRP

If you are not able to attend live lectures and you are completing paper reviews, we will be using HotCRP to organize paper reviews. HotCRP is the software used to manage most conferences in computer science. Through this site, you will be able to submit reviews. We have set up a mock HotCRP for this course:

Course Staff