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       UW CS
       Theory Group

Course Description

Algorithm design and analysis is a fundamental and important part of computer science. This course introduces students to advanced techniques for the design and analysis of algorithms, and explores a variety of applications. Some of the topics we will touch upon are approximation algorithms for NP-hard optimization problems, settings with incomplete knowledge of input (online algorithms), settings with stochastic input, and big data algorithms.

Reference books

There is no textbook for this course. We will read lecture notes from various sources. Here are some useful references for algorithm design basics:
• Rajeev Motwani and Prabhakar Raghavan, Randomized Algorithms, Cambridge University Press, 2000.
• Michael Mitzenmacher and Eli Upfal, Probability and Computing, Cambridge University Press, 2005.
• David Williamson and David Shmoys, The Design of Approximation Algorithms, Cambridge University Press, 2011.
• Jon Kleinberg and Eva Tardos, Algorithm Design, Addison-Wesley, 2006.
• T. Cormen, C. Leiserson, R. Rivest, and C. Stein, Introduction to Algorithms, 2nd edition, 2001.


Prerequisites

One undergraduate course in algorithms (577) or complexity (520, 810, or 830) is required. If you are unsure of whether you have sufficient background for this course or not, please contact the instructor within the first week.

Grading & Evaluation

Homework and exams: There will be 3 homeworks and one take-home final (25% each). The homework can be done in pairs; the take-home final must be done individually.

Contact Info



Instructor:	Shuchi Chawla
Office hours:	W 11 a.m.-noon and R 3-4 p.m.
Location:	CS 4373
Phone:	890-0027
Email:	shuchi (AT) cs (DOT) wisc (DOT) edu