CS 263 - Analysis of Algorithms
Michael T. Goodrich
Office hours: by appointment
General Course Information
- Coursework. Coursework will consist of weekly homeworks,
one midterm exam, and a comprehensive final exam. The overall grade
will be determined 40% from homework, 20% from the midterm, and
40% from the final.
Group work on homeworks is permitted, but each student must
list his or her collaborators in writing for each problem. If a
turns in a solution without listing the others who helped produce
solution, this act will be considered cheating (for it is plagarism).
Late homework assignments will not be accepted.
- Exam policy.
Exam performance must be 100% individual effort; no collaboration
is allowed on exams. Any collaboration or copying on exams will be
In addition to the procedures of the
Cheating Policy, students caught cheating on exams will be given a
failing grade in the class.
Kleinberg and Tardos, Algorithm Design, Addison-Wesley, 2005.
Mitzenmacher and Upfal, Probability and Computing: Randomized
Algorithms and Probabilistic Analysis, Cambridge Univ. Press, 2005.
- Add/drop policy. Drops will be
accepted only up to the end of the third week of class.
Once your drop card has been
signed, further coursework from you will not be graded. After the
seventh week of classes, withdrawals will be allowed only by
petition and under documented extenuating circumstances.
- Week 1:
- Reading: Kleinberg-Tardos, Chapters 1-2.
- Week 2:
- Reading: Kleinberg-Tardos, Chapter 3.
Greedy Algorithms and Divide-and-Conquer.
- Reading: Kleinberg-Tardos, Chapters 4 and 5.
- Reading: Kleinberg-Tardos, Chapter 6.
- Reading: Kleinberg-Tardos, Chapter 8.
- Week 6:
Events and Probability.
- Reading: Mitzenmacher-Upfal, Chapters 1 and 2.
- Week 7:
Chebyshev's Inequality and the Coupon Collectors Problem.
- Reading: Mitzenmacher-Upfal, Chapter 3.
Chernoff Bounds and packet routing.
- Reading: Mitzenmacher-Upfal, Chapter 4.
Balls and Bins.
- Reading: Mitzenmacher-Upfal, Chapter 5.
- Reading: Mitzenmacher-Upfal, Chapter 13.
Copyright © 2009
Michael T. Goodrich, as to all lectures and course content.
Students are prohibited from recording the audio or video content of
lectures and from selling
(or being paid for taking) notes during this course to or by any
person or commercial firm without the express written permission of the
professor teaching this course.