*****COURSES ARE SUBJECT TO CHANGE*****
Rigorous analysis of the time and space requirements of important algorithms, including worst case, average case, and amortized analysis. Techniques include order-notation, recurrence relations, information-theoretic lower bounds, adversary arguments. Analysis of the key data structures: trees, hash tables, balanced tree schemes, priority queues, Fibonacci and binomial heaps. Algorithmic paradigms such as divide and conquer, dynamic programming, union-find with path compression, augmenting paths. Selected advanced algorithms. Introduction to NP-completeness. Enrollment restricted to graduate students; undergraduate students may enroll in this course if they have completed either course 102 or Computer Engineering 177 and have the consent of the instructor.
5 Credits
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2018-19 |
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2017-18 |
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2016-17 |
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2015-16 |
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2014-15 |
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2013-14 |
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2012-13 |
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2011-12 |
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2010-11 |
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2009-10 |
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2008-09 |
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2007-08 |
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2006-07 |
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2005-06 |
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2004-05 |
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2003-04 |
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2002-03 |
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2001-02 |
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2000-01 |
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1999-00 |
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1998-99 |
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