CSE 6512 Randomization in Computing

Fall 2011

Instructor: Sanguthevar Rajasekaran (RAJ, equivalently);

Office Hours: M W 2:00 to 3:30 PM, 257, ITEB, 6-2428; rajasek@engr.uconn.edu

Randomization is a powerful technique that has found applications in varying domains of science and engineering. Testing whether a given integer is a prime, several difficult optimization problems, protein folding, sorting a given sequence, n-body simulations, flow dynamics, linear programming problems, maximum matching, early vision problems such as histograms computation, and data mining are only a few of the numerous problems that have been solved using randomization. In this course we introduce some basic as well as advanced topics in randomization.

Topics to be Covered include Basics of probability theory, Different types of randomization, Some simple problems, Sorting and selection, Hashing and skip list, Finger-printing, Packet routing, Parallel algorithms, Combinatorial optimization, External memory algorithms, etc.

Pre-requisite: Exposure to data structures and algorithms will be helpful.

Reading:

1) R. Motwani and P. Raghavan, Randomized Algorithms, Cambridge Univ. Press, 1995.

2) E. Horowitz, S. Sahni, and S. Rajasekaran, Computer Algorithms, Silicon Press, 2008.

3) Additional references will be supplied.