CSE 6311



Spring 2009

 Tuesday, Thursday – 12:30 – 1:50 PM

Location: NH 110

Instructor: Dr. Gautam Das

Office: 302 Nedderman Hall
Phone: 817 272 7595

Office Hours:  Tue 3-4, wed 2-3


 Teaching Assistant: Senjuti Basu Roy Office Hours: Thursday 2-3pm (GeoScience Building Room No 237) Email:senjuti.basuroy [AT) MAVS [dot] UTA [dot] edu

About the Course

This course aims at exploring advanced computation models, theory and advanced algorithm design and analysis techniques that have broad applicability in solving real-life problems in cross-disciplinary areas such as the Internet computing, Web search engines, data mining, bioinformatics, wireless mobile and sensor networks, dynamic resource management, distributed computing, and social networking.



Theory of NP-completeness

- Turing Reductions and the Complexity Hierarchy

- The classes NP, co-NP, NP-Complete, NP-Hard

- Examples of classical NP-Hard problems


Randomized Techniques

- Probabilistic and Game-Theoretic Methods

- Markov Chains and Random Walks

- Randomized Data Structures

- Randomized Geometric and Graph Algorithms


Approximation Techniques

- Polynomial-time approximation schemes (PTAS)

- Dynamic programming

- Greedy paradigm

- Branch and bound


Pre-requisites: CSE 5311 or consent of instructor



Cormen, Leiserson, Rivest, Stein: Introduction to Algorithms. 2nd Edition, The MIT Press, ISBN 0-07-013151-1

Michael R. Garey, David S. Johnson: Computers and Intractability: A guide to the theory of NP-completeness, 1979 W.H. Freeman ISBN 0-7167-1044-7

Jon Kleinberg, Éva Tardos : Algorithm Design, 2005 Addison Wesley Press, ISBN 978-0321295354

Rajeev Motwani, Prabhakar Raghavan: Randomized Algorithms. 1995, Cambridge University Press, ISBN 0-521-47465-5



3 exams (either in class or take home) worth 1/3 weight each


Class Notes:

Introduction to NP-completeness: Giacomo Ghidini. (pdf)

Lecture 2, Alexandra Stefan. (ppt)

Lecture 3, Walter Wilson. (ppt)

Lecture 4, Saravanan. (pdf)

Lecture 5, Vangelis Meci. (pdf)

Lecture 6, Chandrashekar Vijayarenu. (pdf)

Lecture 7, Deepshikha Jha. (ppt)

Lecture 8, Mysore Radhakrishna, Ranganath M. (ppt)

Lecture 9, Kurabalana Hundi Hombe Gowda, Prashanth. (pdf)

Lecture 10, Rachit Shah. (ppt)

Lecture 11, Avinash. (pdf)

Lecture 12, Alexandra Stefan. (ppt)

Lecture 13, Walter Wilson. (ppt)

Lecture 14, Umair Sadiq. (ppt)

Lecture 15, Giacomo Ghidini. (pdf)

Lecture 16, Na Li. (pdf)

Lecture 17 & 18, Arnab Biswas. (pdf)

Lecture 19, Mahadevraj, Mahadevkirthi Kirthi. (ppt)

Lecture 20, Bin Li (pdf)

Lecture 21, chandrashekar vijayraenu (pdf)

Lecture 22, Ranganath M R. (ppt)

Lecture 23, Kurabalana Hundi Hombe Gowda, Prashanth. (ppt)

Lecture 24, Vangjel Meci (ppt)


  • HOMEWORK-1 (doc)
  • HOMEWORK-2 (pdf)
  • Classnotes calendar (excel)
  • Homework-3 , Chapter 1: Exercises 1.1, 1.2, 1.6, Problems 1.1, 1.4, 1.8, 1.9. Chapter 3: Problems 3.2, 3.12.Chapter 4: Exercise 4.3, Problems 4.1, 4.6, 4.9.
  • Exam-1 is being sent to the class. Submission is due tomorrow 12 noon. Electronic submission is highly encouraged. Students are expected to work independently. If they use any external resources except reference books and class notes, they are expected to acknowledge that in their answer paper.
  • Please check this section regularly during the semester for updates and announcements on the course
  • Ethics statement is available here. Please print, sign and submit it to the instructor during class.

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