COMPSCI 237 - Randomized Algorithms

Institution:

Duke University

Subject:

Computer Science

Description:

Models of computation, Las Vegas and Monte Carlo algorithms, linearity of expectation, Markov and Chebyshev inequalities and their applications, Chernoff bound and its applications, probabilistic methods, expanders, Markov chains and random walk, electric networks and random walks, rapidly mixing Markov chains, randomized data structures, randomized algorithms for graph problems, randomized geometric algorithms, number theoretic algorithms, RSA cryptosystem, derandomization. Prerequisite: Computer Science 230. Instructor: Agarwal, Munagala, or Reif

Credits:

3.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

WWW.DUKE.EDU

Phone Number:

(919) 684-8111

Regional Accreditation:

Southern Association of Colleges and Schools

Calendar System:

Semester

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