CS
483 Spring 2016
Design and Analysis of Algorithms
Lecture time: Tuesday and Thursday 10:30am11:45am
Location: Art
and Design Building 2026
Course webpage: http://www.cs.gmu.edu/~lifei/teaching/cs483spring16
Credit: 3
Instructor: Fei Li, Room 5326, Engineering Building, email: lifei@cs.gmu.edu
Office hours: Thursday 12:00pm2:00pm
Teaching assistant: TBD
Office hours: TBD
News:
Course
overview:
In this course, a thorough examination of
several wellknown 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 NPcompleteness.
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 
Topics 
Lecture
Notes 
Scopes 
Assignments 
Notes 
1 
Introduction 
Chapter 1 


2 
Algorithm
Analysis 
Chapter 2.12.3 



3 


Chapter 2.4 


4 
Graphs 
Chapter 3.13.3 



5 


Chapter 3.43.6 


6 





7 





8 





9 
Greedy
Algorithms 
Chapter 4.14.2 



10 





11 

Chapter 4.44.5 



12 





13 Midterm Exam 





14 





15 





16 
Divide
and Conquer 
Chapter 5.15.3 



17 

Master Theorem 



18 





19 
Dynamic Programming 




20 





21 





22 





23 





24 





25 
Network Flows 




26 





27 





28 





Final Exam 





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 or quizzes (10 * 3 ~ 30%)
Midterm exam (30%)
Final exam (40%)
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/honorcode.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.