CSE 736 - Markov Chains: Foundations and Applications
Spring 2003

	Office: 239 Bell Hall 
	Office Hours: Thursdays 1:00-3:00pm
	Phone: 645-3180 x 160 
	Email: hungngo@cse.buffalo.edu 

Website: http://www.cse.buffalo.edu/~hungngo/classes/MarkovChains_Spring03/

Grading: to be done on an S/N (or S/U) basis only.

Time and place: Mondays 2pm-3:20pm and Tuesdays 7pm-8:20pm. Bell 242.

Description:

I shall spend roughly half of the semester presenting the foundations of Markov Chains, both discrete and continuous. An introductory course on probability theory is recommended, but not absolutely required. I shall provide reading materials on basic probability theory.

At the second half, each member of the class presents a paper or a topic which uses Markov chains. They should be in one of two areas: queueing theory and randomized algorithms.

Also, each class member prepares scribe note for at least one lecture. The LATEX template shall be provided. Part of the grading is based on how much effort I have to spend modifying the scribe note. All notes shall be shared to the class.

A list of recommended papers and topics shall also be provided.

Objectives:

• Have fun learning!
• Learn the foundations of stochastic processes and Markov Chains
• Learn their applications to queueing networks and randomized algorithms

Topics (tentative):

• A Brief Introduction to Linear Algebra
• Stochastic processes
• Poisson Processes and the Exponential Distribution
• Discrete time Markov Chains
• Continuous time Markov Chains
• Martingales

Course Load:

• About 50 pages of dense reading per week (i.e. no bed-time reading).
• Each student is expected to do a presentation at some point during the semester, based on:
  • A survey done by the student on a particular topic to be suggested by the instructor or picked by the student but approved by the instructor.
  • A (few) very dense mathematical paper.
  • An open problem solved by the student.

Prerequisites:

• Find learning new things fun.
• Find learning mathematics fun.
• Find solving mathematical puzzles fun.
• Find the instructor funny.

• OK, the real deals are: rudimentary knowledge on linear algebra, algorithms, probability theory. They are not entirely essential to follow things presented in the seminars. Related background materials shall be provided in the forms of small tutorials/notes. You'd have to read them though.