CS 225: Pseudorandomness
Course meetings: Tue-Thu 1-2:30, Maxwell Dworkin 135 (
Office: Maxwell-Dworkin 337
Shopping period office hours: Thu 2/1 2:30-3, Fri 2/2 1-2, Mon 2/5 4-5, Tue 2/6 2:30-4, Wed 2/7 1:30-2.
Teaching Fellows: Kai-Min Chung and Shien Jin Ong
Office: Maxwell-Dworkin 138
E-mail address for questions:
E-mail address for submitting homeworks: email@example.com
Course website: http://www.courses.fas.harvard.edu/4869
Over the past few decades, randomization has become one of the most pervasive paradigms in computer science. Its widespread use includes:
So randomness appears to be extremely useful in these settings, but we still do not know to what extent it is really necessary. Thus, in this course we will ask:
Main Question: Can we reduce or even eliminate the need for randomness in the above settings?
Why do we want to do this? First, essentially all of the applications of randomness assume we have a source of perfect randomness ≠ one that gives "coin tosses" that are completely unbiased and independent of each other. It is unclear whether physical sources of perfect randomness exist and are inexpensive to access. Second, randomized constructions of objects such as error-correcting codes and expander graphs often do not provide us with efficient algorithms for using them; indeed, even writing down a description of a randomly selected object can be infeasible. Finally, and most fundamentally, our understanding of computation would be incomplete without understanding the power that randomness provides.
In this course, we will address the Main Question via a
powerful paradigm known as pseudorandomness.
This is the theory of efficiently generating objects that "look
random", despite being constructed using little or no randomness.
Specifically, we will study several kinds of "pseudorandom" objects,
Each of the above objects has been the center of a large and beautiful body of research, and until recently these corpora were largely distinct. An exciting recent development has been the realization that all four of these objects are almost the same when interpreted appropriately. Their intimate connections will be a major focus of the course, tying together the variety of constructions and applications of these objects we will cover.
The course will reach the cutting-edge of current research
in this area, covering some results from within the last year. At the
same time, the concepts we will cover are general and useful enough that
hopefully anyone with an interest in the theory of computation or combinatorics could find the material appealing.
This is an advanced graduate course, so I will be assuming that you have general "mathematical maturity" and a good undergraduate background in the theory of computation. One concrete guideline is that you should have had a minimum of two other courses in the theory of computation, including at least one graduate course. If you have particularly strong math background, then there can be a bit more flexibility with this. But if you haven't had a prior graduate course in the theory of computation (numbered CS 22x at Harvard), you must come speak to me at office hours before registering for the class.
In terms of topics, I will be assuming familiarity with the following. In all cases (especially complexity theory), the more background you have, the better.
The requirements of the course:
The biweekly problem sets will typically be due on Wednesday by 1 PM. Your problem set solutions must be typed and submitted electronically to firstname.lastname@example.org. You are allowed 12 late days for the semester, of which at most 7 can be used on any individual problem set. (1 late day = 24 hours exactly).
The problem sets will be challenging, so be sure to start
them early. You are encouraged to discuss the course material and the
homework problems with each other in small groups (2-3 people).
Discussion of homework problems may include brainstorming and verbally walking
through possible solutions, but should not include one person telling the
others how to solve the problem. In addition, each person must write up
their solutions independently, and these write-ups should not be checked
against each other or passed around.
There is no textbook for the course, but I will be handing out lecture notes.† The scribe notes from Spring `04 are here.† You may also find the following references useful. Most of them should be in the libraries, on reserve.