CS 483 Fall 2015
Design and Analysis of Algorithms

Lecture time: Tuesday and Thursday 1:30pm - 2:45pm
Location: Art and Design Building L008
Course webpage: http://www.cs.gmu.edu/~lifei/teaching/cs483fall15
Credit: 3 

Instructor: Fei Li, Room 5326, Engineering Building, email: lifei@cs.gmu.edu
Office hours: Wednesday 2:00pm-4:00pm

Teaching assistant: Nate Craun, Room 4456, Engineering Building, email: ncraun@masonlive.gmu.edu

Office hours Thursday 4:00pm-6:00pm


News:

       12/08/2015: Dr. Li holds office hours 12noon-1pm and 3pm-4pm December 10.

       10/22/2015: Assignment 3 is released. The due date is November 3.

       09/29/2015: Assignment 2 is released. The due date is October 8.

       09/15/2015: Dr. Liís office hours are changed to 2pm-4pm Wednesday.

       09/15/2015: Assignment 1ís due date is updated as 09/17/15.

       09/08/2015: Assignment 1 is released. The due date is 09/15/15 09/17/2015.

       09/08/2015: Dr. Li moved one of his office hours from Tuesday to Monday.

       09/03/2015: TA Nate Craunís office hours are 4:00pm-6:00pm Thursdays and his office is Room 4456 Engineering Building


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, greedy algorithms, divide and conquer techniques, dynamic programming, graph algorithms, search strategies, and an introduction to the theory of NP-completeness.

Prerequisites:

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

Textbook:

Algorithm Design by Jon Kleinberg and Eva Tardos, Addison Wesley (2006).

Reserved at the Gateway Library inside the Johnson Center QA76.9.A43 K54 2006

Course materials:

Lectures

Dates

Topics

Lecture Notes

Scopes

Assignments

Notes

1

September 1

Introduction

Representative Problems

Chapter 1

 

Demo

2

September 3

Algorithm Analysis

Analysis

Chapter 2.1-2.3

 

 

3

September 8

 

 

Chapter 2.4

Assignment 1: Page 67, Exercise 3,Page 68, Exercise 6, Page 69, Exercise 8

 

4

September 10

Graphs

Graphs

Chapter 3.1-3.3

 

 

5

September 15

 

 

Chapter 3.4-3.6

 

Assignment 1 is due.

6

September 17

 

 

 

 

Assignment 1 is due.

7

September 22

 

 

 

 

 

8

September 24

 

 

 

 

 

9

September 29

Greedy Algorithms

Greedy Algorithms 1

Chapter 4.1-4.2

Assignment 2: Page 110, Exercise 10,Page 111, Exercise 11, Page 112, Exercise 12

one more problem

 

10

October 1

 

 

 

 

 

11

October 6

 

Greedy Algorithm 2

Chapter 4.4-4.5

 

 

12

October 8

 

 

 

 

Assignment 2 is due.

Columbus Day recess, Tuesday class cancelled

October 13

 

 

 

 

 

13

Midterm Exam

October 15

 

 

 

 

 

14

October 20

 

 

 

 

 

15

October 22

 

 

 

Assignment 3

 

16

October 27

Divide and Conquer

Divide and Conquer 1

Chapter 5.1-5.3

 

17

October 29

 

Divide and Conquer 2

Master Theorem

 

 

18

November 3

 

 

 

 

Assignment 3 is due.

19

November 5

Dynamic Programming

Dynamic Programming 1

 

 

 

20

November 10

 

Dynamic Programming 2

 

 

 

21

November 12

 

 

 

 

 

22

November 17

 

 

 

 

 

23

November 19

 

 

 

 

 

24

November 24

 

 

 

 

 

Thanksgiving recess

November 26

 

 

 

 

 

25

December 1

Network Flows

Network Flows 1

Demo

 

 

 

26

December 3

 

Network Flows 2

 

 

 

27

December 8

 

 

 

 

28

December 10

 

 

 

 

Final Exam

December 15

(1:30pm Ė 4:15pm)

 

 

 

 

 

 

Topics:

In this course, we will consider the algorithm design and analysis 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)

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

Course outcomes:

An understanding of classical problems in Computer Science

An understanding of classical algorithm design and analysis strategies

An ability to analyze the computability of a problem

Be able to design and analyze new algorithms to solve a computational problem

An ability to reason algorithmically

Tentative grading:

Weekly assignments (12 * 3 ~ 35%)

Midterm exam (30%)

Final exam (35%)

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.