Instructor: Ivona Bezakova, email: here.
Class meets: Mo/We 6-8pm, room 70-1455
Office hours: Mo 3-5pm, Tu 10am-12pm, office
Tutoring center: about 20 hours of tutoring per week
(follow this link
to see the schedule and more information)
0. Homework and Reading
For information about topics covered in the class,
reading and homework assignments, follow this
to Algorithms by Cormen, Leiserson, Rivest, and Stein, Second Edition.
2. Course description and intended learning outcomes.
This course provides an introduction to the design and analysis of algorithms.
It covers a large number of classical algorithms and their complexity and will
equip students with the intellectual tools to design, analyze, implement, and
evaluate their own algorithms.
Intended learning outcomes:
Students should demonstrate an understanding of basic concepts related to the design and analysis of algorithm.
Students should demonstrate knowledge of classical algorithms and their complexity.
Students should be able to design and analyze their own algorithms.
Students should implement, experiment with, compare, and report on various algorithmic solutions to the same problem.
3. Grading Policy
Grading scale: 90%-100%: A, 80%-90%: B, 70%-80%: C, 60%-70%: D, 0%-60%: F.
The midterm will be held in class, on January 22, 2007.
the date of the midterm has changed from the originally proposed January 17,
based on your vote in class).
If your score on the final is better than on the midterm, your
final will contribute 40% toward your final grade and your midterm
will contribute 20%.
There will be eight weekly homeworks, due Wednesday 6pm (every week except for the 1st and 5th week).
Homework assignments will be posted on the webpage a week before they are due.
The two lowest homework grades will be dropped and
the remaining six grades contribute evenly towards your final grade.
There will be a programming project which will be specified in the 3rd week and it will be due
February 12, 2007.
However, your overall grade cannot be more than one letter better than your average exam grade. Moreover, average exam grade F results in failing the class.
- Minimum spanning trees
- Single source shortest path
- All pairs shortest path
- Network flow
Overview of heuristics and approximation
Other topics such as linear programming and randomized algorithms.
Please e-mail me any other topics you would like to see discussed in class.
5. Technical issues
Discussing homework with your fellow students is encouraged. However, after such discussions, all notes must be discarded, blackboards erased, and every student must write up their solutions in private without further consultations with your classmates or any written material other than your notes, the textbook or this webpage. For every problem discussed with other students, state their names and briefly sketch the extent of your discussions (e.g. "solved together", or "clarified problem statement").
All homeworks are due on Wednesdays, 6pm. No late submissions will be tolerated. I will stop answering homework
related e-mails on Wednesday, 12pm. You will have a week to complete each homework and the assignments will be
posted on the webpage on Wednesdays.
Exams are closed book, closed notes. You may prepare one letter-size hand-written "summary sheet" (no photocopies).
- Homework or exam grade can be disputed within one week after the graded work is handed back. Dispute the grade with the instructor, not the grader. Your grades will be posted on MyCourses.
The midterm and the final cannot be made up unless a true emergency arises (a proper documentation is required in such cases).
- Hopefully there is no need to link to the departmental policy on academic dishonesty. In the unfortunate event when cheating earns a 0 score on a homework, the two lowest non-cheating scores will be dropped.