http:^^cs.nyu.edu^cs^dept_info^course_home_pages^spr97^g22.3033.01^index.html

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Date: Tue, 26 Nov 1996 18:49:54 GMTServer: NCSA/1.4.1Content-type: text/htmlLast-modified: Tue, 19 Nov 1996 18:14:11 GMTContent-length: 1753<HEAD><TITLE>Syllabus</TITLE></HEAD><BODY><P><H3> <b>Randomized Algorithms</b></H3><P><P><b>Instructor</b>.  Richard Cole, WWW412, tel: 998-3119, cole@cs.nyu.edu.<P><b>Syllabus</b>.Randomization is a powerful tool for achieving efficiency and/orsimplicity in many settings.This course will study a variety of techniques for usingrandomization in algorithm design.Randomization typically introduces uncertainty, which couldbe uncertainty regarding the result, or uncertainty regarding thealgorithm's performance; but this is tolerable if it is ofsufficiently low probability.Primality testing and quicksort, respectively,provide examples of each of these.Techniques for analyzing the (probabilistic) correctness andperformance of randomized algorithms will be a centralpart of the course.<p><b>Prerequisites</b>.Honors Analysis of Algorithms, or A in Fundamental Algorithms,or equivalent background with permission of the instructor.The course also assumes familiarity with basic probability andcounting, such as might be encoutered in an analysis of quicksortor of an idealized hashing scheme.<p><b>Assignments</b>.There will be homeworks comprisingproblems drawn from the textbook and elsewhere.Late homeworks will not be accepted (except in the event ofillness of other unavoidable circumstances).If for some reason you will be unable to hand in a homework on time,please discuss it with me beforehand.<p><b>Required text</b>.Motwani and Raghavan, Randomized Algorithms.<p><p><p><!WA0><a href="http://cs.nyu.edu/">CS Department</a>,<!WA1><a href="http://www.nyu.edu/">NYU</a><p><font=-1><!WA2><a href=mailto:cole@cs.nyu.edu>cole@cs.nyu.edu</a> (Richard Cole)<br>Last modified: Nov 11, 1996</I></ADDRESS></BODY>

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