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: Tuesday
3:00pm – 4:00pm
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, 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 Éva Tardos, Addison Wesley (2006).
Course
materials:
|
Lectures |
Dates |
Topics |
Lecture
Notes |
Scopes |
Assignments |
Notes |
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1 |
September
1 |
Introduction |
Chapter 1 |
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2 |
September
3 |
Algorithm
Analysis |
Chapter 2.1-2.3 |
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3 |
September 8 |
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Chapter 2.4 |
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4 |
September 10 |
Graphs |
Chapter 3.1-3.3 |
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5 |
September 15 |
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Chapter 3.4-3.6 |
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6 |
September 17 |
Greedy
Algorithms |
Chapter 4.1-4.2 |
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7 |
September 22 |
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Chapter 4.3-4.5 |
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8 |
September 24 |
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9 |
September 29 |
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10 |
October 1 |
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11 |
October 6 |
Divide
and Conquer |
Chapter 5.1-5.3 |
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12 |
October 8 |
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Columbus Day recess, Tuesday class cancelled |
October
13 |
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Master Theorem |
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13 |
October 15 |
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14 |
October 20 |
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15 |
October 22 |
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16 |
October 27 |
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17 |
October 29 |
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18 |
November 3 |
Dynamic Programming |
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19 |
November 5 |
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20 |
November 10 |
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21 |
November 12 |
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22 |
November 17 |
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23 |
November 19 |
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Thanksgiving recess |
November 24 |
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Thanksgiving recess |
November 26 |
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24 |
December 1 |
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25 |
December 3 |
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26 |
December 8 |
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27 |
December 10 |
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28 Final Exam |
December 15 (1:30pm – 4:15pm) |
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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 (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/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.