CS331: ALGORITHMS AND COMPLEXITY, Spring 2017

Professor Vijaya Ramachandran

Department of Computer Science, UT-Austin

COURSE DESCRIPTION 

Time/Location/Unique number. MW 11-12:30, MEZ B0.306, unique numbers 52066 and 52067.

Discussion Sessions. #52066 F 1-2  in JGB 2.202; #52067 F 2-3 in  JGB 2.202.

Prerequisites. The following coursework with a grade of at least C-:  Computer Science 429 (or 310) or 429H (or 310H); Mathematics 362K or Statistics and Data Sciences 321 (or Statistics and Scientific Computation 321); and credit with a grade of at least C- or registration for: Mathematics 340L, 341, or Statistics and Data Sciences 329C (or Statistics and Scientific Computation 329C).

Professor. Vijaya Ramachandran (vlr"at"cs, GDC 4.430, 471-9554)
Office Hours. TBD.

Teaching Assistant. Udit Agarwal (udit"at"cs.utexas.edu)
TA Office Hours.  TBD.

Textbook.  Jon Kleinberg and Eva Tardos, Algorithm Design, Pearson Education, 2006.

COURSE OUTLINE. This course will cover the basic aspects of the theory of algorithms, including divide-and-conquer, greedy, and dynamic programming, several graph algorithms, randomized algorithms, and approximation algorithms, together with an introduction to undecidability, and to NP-completeness. Here is a high-level course schedule. 

COURSE SCHEDULE.  

Introduction;  graph searching

1 week

Greedy algorithms; minimum spanning tree; Dijkstra's SSSP

2 weeks

Divide and conquer; recurrence relations  

1 week 

Dynamic programming; shortest paths in graphs 

2 weeks 

NP-completeness 

2 week 

Approximation algorithms

1 week 

Undecidability; halting problem

1 week 

Randomized algorithms; hashing 

2 weeks 

Maximum flow, bipartite matching  

1 week 


This is a theory course and there is no programming content. This course carries the Quantitative Reasoning (QR) flag: establishing the correctness of algorithms and rigorous bounds on their running times, and deriving proofs of NP-completeness and undecidability are important components of this course. 

Coursework. The course grade will be based on the following coursework. 

Course Grade. The course grade will be computed as follows: 


Key Dates. (Please make a note of these dates -- there will be no make-up test or exam.)

Additional Information on Coursework. 


Canvas. All class-related course material will be on Canvas.

Piazza Discussion Board. We will use Piazza for discussions. Please reserve your email messages to the instructor and TA for matters that concern only you. For queries relating to class material, please post to the discussion board on Piazza so that everyone can benefit from the query and the responses. Students are encouraged to post comments and queries about class material on the Piazza discussion board. 

Grading Queries. Any questions on grading should be brought to the attention of the TA or the instructor no later than a week after the graded material is returned to the class. 

Students with Disabilities. Students with disabilities may request appropriate academic accommodations from the Division of Diversity and Community Engagement, Services for Students with Disabilities, 471-6259, http://www.utexas.edu/diversity/ddce/ssd
If you intend to notify me of such accommodations, please do so by February 1. 

Accommodations for Religious Holidays. If you must miss a class or an examination in order to observe a religious holy day, you will be given an opportunity to complete the missed work within a reasonable time before or after the absence.
If you intend to make use of such accommodations, please let me know by February 1. 

Statement on Scholastic Dishonesty. Anyone who violates the rules for the problem sets or who cheats in the  tests or final exam is in danger of receiving an F for the course. Additional penalties may be levied by the Computer Science Department and the University.
The departmental code of conduct posted at http://www.cs.utexas.edu/academics/conduct will apply unless superseded by the rules stated for this course in this course description.