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×Davis, California•
Theory and practice of hard problems, and problems with complex algorithm solutions. NP-completeness, approximation algorithms, randomized algorithms, dynamic programming and branch and bound. Theoretical analysis, implementation and practical evaluations. Examples from parallel, string, graph, and geometric algorithms.
Units: 4.0
Hours: Lecture—3 hour(s); Discussion—1 hour(s).