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Justin Hsu 4 years ago
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      website/docs/format.md
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      website/docs/syllabus.md

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Lectures will be loosely organized around four modules: differential privacy,
cryptography, language-based security, and adversarial machine learning. I will
give most of the lectures for the first module, on differential privacy. For
each of the remaining modules, I will give the first lecture introducing the
topic and background material. Then, each student will lead one lecture,
Lectures will be loosely organized around **four modules**: differential
privacy, 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 introductory lecture surveying
the topic and background material. Then, each student will lead one lecture,
presenting a paper and guiding the discussion.
The topics we will be reading and thinking about are from the recent research
literature---polished enough to be peer-reviewed and published, but not always
completely refined. Given that this is a graduate course, not all lectures are
set in stone and there is considerable flexibility in the topics. If you are
interested in something not covered in the syllabus, please let me know.
This is a graduate seminar, so not all lectures are set in stone and there is
considerable flexibility in the topics. 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 lecture presenting a paper, students are expected to read the paper
closely and understand its significance, including (a) the problem addressed by
the paper, (b) the main contributions of the paper, and (c) how the authors
solve the problem in some technical detail.
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
**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---polished enough to be 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** the
questions at least 24 hours before every paper presentation. **Before** eah
lecture, you should send me brief answers---a short email is fine, no more than
a few sentences per question. These questions are for your benefit---they are
not meant to be very difficult or time-consuming and they will not be graded in
@ -36,11 +36,11 @@ detail.
## Course Project
The other main component is the course project. You will work individually or in
pairs on a topic of their choice, producing a conference-style write-up and
presenting their project at the end of the semester. This project should have
the potential to turn into a research paper or survey. Details can be found
[here](projects/details.md).
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
@ -54,4 +54,4 @@ Grades will be assigned as follows:
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 beforehand.
check with me first.

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website/docs/syllabus.md

@ -9,8 +9,9 @@ make decisions in critical sectors (e.g., health care, automation, and
finance). However, in deploying these algorithms presence of malicious
adversaries is generally ignored.
This advanced topics class will tackle techniques related to all these
themes. We will cover the following broad topics.
This advanced topics class will tackle techniques related to all these themes.
We will cover topics drawn from the following broad areas, depending on student
interests:
### Differential Privacy
- Basic properties and examples

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