Note: You are looking at a static copy of the former PineWiki site, used for class notes by James Aspnes from 2003 to 2012. Many mathematical formulas are broken, and there are likely to be other bugs as well. These will most likely not be fixed. You may be able to find more up-to-date versions of some of these notes at http://www.cs.yale.edu/homes/aspnes/#classes.

1. Course textbook

Rajeev Motwani and Prabhakar Raghavan, Randomized Algorithms. Cambridge University Press, 1995. ISBN 0521474655. QA274 M68X 1995. Also available on-line from Yale campus IP addresses.

2. Useful probability theory refererences

Michael Mitzenmacher and Eli Upfal. Probability and Computing: Randomized Algorithms and Probabilistic Analysis. Cambridge University Press, 2005. ISBN 0521835402. QA274 .M574X 2005. Also available on-line from Yale campus IP addresses. Reasonably good introductory text on analysis of randomized algorithms with an emphasis on allocation problems.

William Feller, An Introduction to Probability Theory and Its Applications, volumes 1 and 2. Wiley, 1968 (volume 1, 3rd edition); Wiley 1971 (volume 2, 2nd edition). QA273 F43 1968. The probability theory analog of Knuth's Art of Computer Programming: comprehensive, multiple volumes, every theoretical computer scientist of the right generation owns a copy. Volume 1, which covers discrete probability, is the most useful for computer science.

Geoffrey R. Grimmett and David R. Stirzaker, Probability and Random Processes. Oxford University Press, 2001. ISBN 0198572220. QA273 G74X 2001. Similar in scope to Feller. A good alternative if you are on a budget.