Polishing.
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Lectures will be loosely organized around four modules: differential privacy,
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cryptography, language-based security, and adversarial machine learning. I will
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give most of the lectures for the first module, on differential privacy. For
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each of the remaining modules, I will give the first lecture introducing the
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topic and background material. Then, each student will lead one lecture,
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Lectures will be loosely organized around **four modules**: differential
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privacy, cryptography, language-based security, and adversarial machine
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learning. I will give most of the lectures for the first module (differential
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privacy). For the other modules, I will give an introductory lecture surveying
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the topic and background material. Then, each student will lead one lecture,
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presenting a paper and guiding the discussion.
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The topics we will be reading and thinking about are from the recent research
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literature---polished enough to be peer-reviewed and published, but not always
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completely refined. Given that this is a graduate course, not all lectures are
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set in stone and there is considerable flexibility in the topics. If you are
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interested in something not covered in the syllabus, please let me know.
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This is a graduate seminar, so not all lectures are set in stone and there is
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considerable flexibility in the topics. If you are interested in something not
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covered in the syllabus, please let me know!
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## Readings and Homework
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Paper discussions are a core component of this course. You are expected to read
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papers before lecture, attend lectures, and participate in discussions. Before
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every lecture presenting a paper, students are expected to read the paper
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closely and understand its significance, including (a) the problem addressed by
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the paper, (b) the main contributions of the paper, and (c) how the authors
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solve the problem in some technical detail.
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**Paper discussions** are a core component of this course. You are expected to
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read papers before lecture, attend lectures, and participate in discussions.
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Before every paper presentation, students are expected to read the paper closely
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and understand its significance, including (a) the main problem addressed by the
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paper, (b) the primary contributions of the paper, and (c) how the authors solve
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the problem in some technical detail.
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Most research papers focus on a very narrow topic and are written for a very
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specific technical audience. It also doesn't help that computer science
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researchers are generally not the clearest writers (though there are certainly
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exceptions!). These
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The topics we will be reading and thinking about are from the recent research
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literature---polished enough to be peer-reviewed and published, but not always
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completely refined. Most research papers focus on a very narrow topic and are
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written for a very specific technical audience. It also doesn't help that
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computer science researchers are generally not the clearest writers (though
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there are certainly exceptions). These
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[notes](https://web.stanford.edu/class/ee384m/Handouts/HowtoReadPaper.pdf) by
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Srinivasan Keshav may help you get more out of reading papers.
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To help you prepare for the class discussions, I will also send out a few
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questions at least 24 hours before every paper presentation. **Before** the
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questions at least 24 hours before every paper presentation. **Before** eah
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lecture, you should send me brief answers---a short email is fine, no more than
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a few sentences per question. These questions are for your benefit---they are
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not meant to be very difficult or time-consuming and they will not be graded in
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@ -36,11 +36,11 @@ detail.
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## Course Project
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The other main component is the course project. You will work individually or in
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pairs on a topic of their choice, producing a conference-style write-up and
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presenting their project at the end of the semester. This project should have
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the potential to turn into a research paper or survey. Details can be found
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[here](projects/details.md).
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The other main component is the **course project**. You will work individually
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or in pairs on a topic of your choice, producing a conference-style write-up and
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presenting the project at the end of the semester. Successful projects may have
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the potential to turn into an eventual research paper or survey. Details can be
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found [here](projects/details.md).
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## Grading and Evaluation
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The final project may be done individually or in groups of two students.
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Collaborative projects with people outside the class may be allowed, but please
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check with me beforehand.
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check with me first.
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@ -9,8 +9,9 @@ make decisions in critical sectors (e.g., health care, automation, and
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finance). However, in deploying these algorithms presence of malicious
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adversaries is generally ignored.
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This advanced topics class will tackle techniques related to all these
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themes. We will cover the following broad topics.
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This advanced topics class will tackle techniques related to all these themes.
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We will cover topics drawn from the following broad areas, depending on student
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interests:
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### Differential Privacy
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- Basic properties and examples
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