Instructors:
Michael Kearns
and
Aaron
Roth
Time: Friday 12:00-3:00
Room: Levine 512
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Overview: In
this class we will study applications of the remarkable
multiplicative weights update
method and related techniques to computer science.
Application areas include game theory and mechanism design, learning
theory, complexity theory, combinatorial optimization, differential
privacy, and more. The class will be run in a seminar style. The
instructors will give the first two lectures, and after that, students
will choose papers to read and present. The entire class is expected to
-read- the paper being presented that week, but the presenter will have
the responsibility of teaching the material. We will have occasional
guest lectures from experts.
Prerequisites:
This will be a
mathematically rigorous
theory
course intended for graduate students. There are no formal
prerequisistes other than mathematical maturity. You should be
comfortable reading and presenting formal mathematical material at a rigorous level.
Goals and Grading:
Grading will be on the basis of your presentations as well as
participation during the presentations of others.
Textbook:
There will be no textbook, but we will be loosely following
the
survey paper of Arora, Hazan, and Kale. (AHK) Other useful
references will be
Chapter
4 of Algorithmic Game Theory (BM) by Blum and
Mansour, and the textbook "
Boosting"
(SF), by Schapire and Freund.
Office Hours:
By appointment