CS 174
Combinatorics and Discrete Probability
Spring 2002

.
[Lecture Notes]
[Homework]
[Recitation Notes]
People
Professor:
Michael Jordan
(jordan@eecs.berkeley.edu)
Office: 731 Soda, 23806
Office hours: M 2:303:30 (731 Soda), T 12 (401 Evans)
TA:
Hao Zhang (nhz@eecs.berkeley.edu)
Office: 547 Soda, 26193
Office hours: M 45, Th 45
Description
An introduction to probabilistic methods and their applications in computer
science.
Theory: basic probability
theory; combinatorics and probability; Markov, Chebyshev, and other moment
inequalities; large deviations; limited dependence; conditional expectation;
martingales; the probabilistic method; Markov chains; fingerprinting; probability
amplification and derandomization
Applications: sorting; data structures;
pattern matching; graph algorithms; errorcontrol coding; parallel and
distributed algorithms; online algorithms; zeroknowledge
proofs; electronic voting; digital cash
Textbooks
Motwani and Raghavan, Randomized Algorithms, Cambridge University
Press, 1995.
Prerequisites
The prerequisites are an upper division course on algorithms (CS 170 or
equivalent) and a course on discrete mathematics including basic probability
(Math 55 or equivalent).
Grading
There will be two quizzes and a final exam. Each quiz will count for 15%
of your grade, the final will count for 35% and the homeworks will count
for 35%.
Quizzes
The dates for the quizzes are Monday, Feb. 25, and Wednesday, Apr. 3.
Homework
There will be (roughly) weekly homework assignments, due one week after
being passed out. Late homeworks will not be accepted.
You should try to solve problems on your own. If you discuss problems
with another student, indicate on your writeup the name of your collaborator(s).
In any case you must write up your own solutions.
Website and newsgroup
The course website is:
http://www.cs.berkeley.edu/~jordan/courses/174spring02
and the course newsgroup is
ucb.class.cs174