CS 483 Syllabus (Fall 2009)

CS 483 Fall 2009
Design and Analysis of Algorithms

Lecture Time: Monday and Wednesday 3:00pm - 4:15pm
Location: Innovation Hall 134
Course webpage: http://www.cs.gmu.edu/~lifei/teaching/cs483_fall09/
Credit: 3

Instructor: Fei Li, Room 5326, Engineering Building, email: lifei@cs.gmu.edu
Office hours: Thursday 4:30pm - 6:30pm; Teaching Assistant: TBD; Office hours: TBD
NEWS:

Course Overview:: In this course, a thorough examination of several well-known techniques that are used for the design and analysis of efficient algorithms will be covered. Topics to be covered include theoretical measures of algorithm complexity, sorting and selection algorithms, greedy algorithms, divide and conquer techniques, dynamic programming, linear programming, graph algorithms, search strategies, and an introduction to the theory of NP-completeness, algorithms for algebraic problems, probabilistic methods, and approximation algorithms.

Prerequisites:: CS 310 and CS 330 Calculus (MATH 113, 114, 213) and MATH 125. Please contact with the instructor if you are not sure.

Required Textbook:

Algorithms by S. Dasgupta, C.H. Papadimitriou, and U.V. Vazirani, The McGraw-Hill Companies (2008). A draft of the book can be found at http://www.cs.berkeley.edu/~vazirani/algorithms.html

Highly Recommended Textbook:

Course Materials:

Lecture	Date	Topic	Lecture Notes	Scope	Assignments	Note
1	Aug. 31	Introduction
2	Sep. 2
	Sep. 7					No class. Labor Day
3	Sep. 9
4	Sep. 14
5	Sep. 16
6	Sep. 21
7	Sep. 23
8	Sep. 28
9	Sep. 30
10	Oct. 5
11	Oct. 7
	Oct. 12					No class. Columbus Day
12	Oct. 13	Review				Monday class meets Tuesday
13	Oct. 14	Midterm
14	Oct. 19
15	Oct. 21
16	Oct. 26
17	Oct. 28
18	Nov. 2
19	Nov. 4
20	Nov. 9
21	Nov. 11
22	Nov. 16
23	Nov. 18
24	Nov. 23
	Nov. 25					No class. Thanksgiving.
25	Nov. 30
26	Dec. 2
27	Dec. 7	Review
28	Dec. 9					No class. Reading days.
29	Dec. 14	Final exam				1:30 pm – 4:15 pm

Topics:

In this course, we will consider the algorithm design and alaysis techniques of various problems coming from the following areas:

• Analysis of Algorithm Efficiency (asymptotic notation, amortized analysis)
• Brute Force Techniques (sorting, search, traveling salesmen)
• Divide and Conquer (merge sort, quicksort, matrix multiplication, polynomial multiplication)
• Numerical algorithms (modulo arithmetic, RSA)
• Graph decomposition and search (connected components, shortest path problem)
• Greedy Techniques (minimum spanning tree, Huffman trees)
• Dynamic Programming (edit distance,matrix chainmultiplication, knapsack, all pairs shortest paths)
• Linear Programming (network flows, matching, simplex, duality)
• Randomized Algorithms
• Limitations of Algorithm Power (lower bounds, P, NP)
• Coping with Limitations (approximation algorithms)

Course Outcomes:

1. An understanding of classical problems in Computer Science
2. An understanding of classical algorithm design and analysis strategies
3. An ability to analyze the computability of a problem
4. Be able to design and analyze new algorithms to solve a computational problem
5. An ability to reason algorithmically

Tentative Grading:

Policies:
: Hand in hard copies of assignments in class. Please note that all coursework is to be done independently. Plagiarizing the homework will be penalized by maximum negative credit and cheating on the exam will earn you an F in the course. See the GMU Honor Code System and Policies at http://www.gmu.edu/catalog/acadpol.html and http://www.cs.gmu.edu/honor-code.html. You are encouraged to discuss the material BEFORE you do the assignment. As a part of the interaction you can discuss a meaning of the question or possible ways of approaching the solution. The homework should be written strictly by yourself. In case your solution is based on the important idea of someone else please acknowledge that in your solution, to avoid any accusations.

Academic Honesty:

The integrity of the University community is affected by the individual choices made by each of us. GMU has an Honor Code with clear guidelines regarding academic integrity. Three fundamental and rather simple principles to follow at all times are that: (1) all work submitted be your own; (2) when using the work or ideas of others, including fellow students, give full credit through accurate citations; and (3) if you are uncertain about the ground rules on a particular assignment, ask for clarification. No grade is important enough to justify academic misconduct.

Plagiarism means using the exact words, opinions, or factual information from another person without giving the person credit. Writers give credit through accepted documentation styles, such as parenthetical citation, footnotes, or endnotes. Paraphrased material must also be cited, using MLA or APA format. A simple listing of books or articles is not sufficient. Plagiarism is the equivalent of intellectual robbery and cannot be tolerated in the academic setting. If you have any doubts about what constitutes plagiarism, please see me.

Disability Statement:

If you have a learning or physical difference that may affect your academic work, you will need to furnish appropriate documentation to the Disability Resource Center. If you qualify for accommodation, the DRC staff will give you a form detailing appropriate accommodations for your instructor.

In addition to providing your professors with the appropriate form, please take the initiative to discuss accommodation with them at the beginning of the semester and as needed during the term. Because of the range of learning differences, faculty members need to learn from you the most effective ways to assist you. If you have contacted the Disability Resource Center and are waiting to hear from a counselor, please tell me.