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About the Course
The following is a tentative list of topics which we will attempt
to cover:
- Probabilistic and Game-Theoretic Methods
- Markov Chains and Random Walks
- Randomized Data Structures
- Randomized Geometric and Graph Algorithms
- Approximation Methods
We will cover various topics in breadth, understand the central
contributions of these efforts and try and predict future research
directions.
Prerequisites
Pre-requisites: CSE 5311 or consent of instructor
Text
Book
Rajeev Motwani, Prabhakar Raghavan: Randomized Algorithms. 1995, Cambridge University Press, ISBN
0-521-47465-5
Evaluation
The grade will be based on class participation, attendance and
exams conducted over the course of the semester.
Questions
for Final Exam: 8.5, 8.7, 10.7, 10.8,
10.13, and 10.15
Guidelines for Final Exam: (a) work on your own, and
(b) do not attempt to use material on the internet. If you do any of
these, you should clearly acknowledge it on your answers.
Answers
are due Wednesday at Noon!
Class
Notes:
Lecture 1: Muhammed Miah. (ppt)
(pfd)
Lecture 2: Xin Jin. (ppt)
(pdf)
Lecture 3: Arjun Dasgupta. (ppt)
(pdf)
Lecture 4: Raghu (ppt)
(pdf)
Lecture 5: Lekhendro (ppt)
Lecture 6: Senjuti (ppt)
(pdf)
Lecture 7: Parth (ppt)
Lecture 8: Payoj (pdf)
Lecture 9: Rachit
Lecture 10: Anirban
Lecture 11: Manoj
Lecture 12: Muhammed Miah
Lecture 13: Xin Jin
Lecture 14: Arjun Dasgupta
Lecture 15: Raghu
Lecture 16: Lekhendro
Announcements
- 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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