[2012 Fall]
COT-6405-U01: Analysis of Algorithms

SYLLABUS | SCHEDULE | ANNOUNCEMENTS


Conference: GL139, T/R 12:30-1:45PM

Instructor: Dr. Wei Zeng

Office: ECS 357

Office Hours: T/R 3:00-5:30PM

Homepage: http://www.cis.fiu.edu/~wzeng/

TA: Rong Rong

Email: rrong001@


[Syllabus]

Announcements

11/25: Final Exam will be taken at 12:00-14:00PM, Dec 04, 2012, GL 139!  

11/20: Assignment#06 has been posted to Moodle! Due date: Thursday 11:59PM, Nov 29, 2012. 

11/15: Quiz#01-Solution has been posted to Moodle!

11/12: Quiz#02 (take-home) has been posted to Moodle! Due date: Monday 11:59PM, Nov 26, 2012.

11/12: Assignment#05 has been posted to Moodle! Due date: Monday 11:59PM, Nov 19, 2012.

10/28: Assignment#04 has been posted to Moodle! Due date: Sunday 11:59PM, Nov 04, 2012.

10/21: Assignment#03 has been posted to Moodle! Due date: Sunday 11:59PM, Oct 28, 2012.

10/02: Quiz#01 will be taken in class on Tuesday 12:30-1:45PM, Oct 09, 2012.

09/23: Assignment#02 has been posted to Moodle! Due date: Sunday 11:59PM, Oct 07, 2012.

09/20: Lectures#01-10 have been posted to Moodle!  

09/02: Assignment#01 has been posted to Moodle! Due date: Sunday 11:59PM, Sep 16, 2012.


Lecture Schedule

Notes: More course materials can be found in Moodle.

08/21: Lecture#01: Introduction, Insertion Sort

08/23: Lecture#02: Divide-and-Conquer, Merge Sort

08/28: Lecture#03: Asysmptotic Notation

08/30: Lecture#04: The Master Theorem, Probability Analysis & Randomized Algorithms

09/04: Lecture#05: Heapsort

09/06: Lecture#06: Quicksort

09/11: Lecture#07: Analysis of Quicksort, Lower Bound for Comparison Sort

09/13: Lecture#08: Sorting in Linear Time

09/18: Lecture#09: Medians and Order Statistics

09/20: Lecture#10: Elementary Data Structures, Binary Search Tree

09/25: Lecture#11: Binary Search Tree, Red Black Tree

09/27: Lecture#12: Red Black Tree, Requirements of Assignment#02

10/02: Lecture#13: Hash Table, Direct Addressing Table, Chaining

10/04: Lecture#14: Hash Functions, Open Addressing, Universal Hashing & Perfect Hashing

10/09: Quiz#01: Part I, Part II, Part III (BST, RBT)

10/11: Lecture#15: Augmenting Data Structures

10/16: Lecture#16: Dynamic Programming, Cutting Rod, Longest Common Subsequence

10/18: Lecture#17: Greedy Algorithms, Activity-Selection Problem

10/23: Lecture#18: Amortized Analysis, Table Expansion

10/25: Lecture#19: Linear Programming

10/30: Lecture#20: Advanced Data Structures: B-Trees

11/01: Lecture#21: B-Trees, Fibonacci Heaps

11/06: Lecture#22: Fibonacci Heaps

11/08: Lecture#23: Graph Algorithms: Maximum Flow

11/13: Lecture#24: Algorithms for Maximum Flow

11/15: Lecture#25: Algorithm Analysis in Max-Flow Problem, Breadth First Search, Shortest Path Distance

11/20: Summary & Evaluation 

11/27: OfficeReview & Discussion

11/29: OfficeReview & Discussion 

12/04: Final Exam


Topics

Notes: (*) denotes the number of classes on the corresponding topic.

Introduction: Asymptotic Analysis  (2)

Divide-and-Conquer Paradigm & Randomized Algorithms  (2)

Sorting and Order Statistics  (5)

Data Structures  (6)

Dynamic Programming, Greedy Algorithms, Amortized Analysis  (3)

Linear Programming  (1)

Advanced Data Structure  (3)

Graph Algorithms  (3)


Catalog Decription

Design of advanced data structures and algorithms; advanced analysis techniques; lower bound proofs; advanced algorithms for graph, string, geometric, and numerical problems; approximation algorithms; randomized and online algorithms. (3 credits)


Textbook

[CLRS] Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. Introduction to Algorithms, Third Edition, MIT Press. 2009.


Prerequisites

SCIS Graduate Standing, esp., Data Structure, Computer Programming, Algebra, Probability Analysis


Type

Required for MSCS 

Elective for MSIT, MSTN, and Ph.D. students 


Course Objectives

Students will learn both the elementary and advanced techniques for efficient algorithm design along with asymptotic analysis of running time or cost and intractability proof for real problems.


Reference

[KT] Kleinberg and Tardos. Algorithm Design, Addison-Wesley. 2005.


Grading Policy

Homework (problem sets / programming): 30%    

Quiz 1 (in-class): 15%

Quiz 2 (take-home): 15%  

Final Exam (in-class): 35%  

Participation: 5% 

Notes: All the homework/Quzi-2 assignment, submission, and grading will be done through Moodle.

1. The due date for homework will be announced with homework assignment. Late homework will generanlly not be accepted. If there are extenuating circumstances, you should make prior arrangements with TA.

2. The answers to problem set are required to be uploaded to Moodle. TA will evaluate them and post grades there. 

3. All the homework should be finished independently.

4. The take-home Quiz-2 can be done independently or in a form of study group, but finally the answer should be written down independently in your own words.

5. If writing your problem set by hand, it is a good idea to copy over your answers and scan it for uploading which will make your work neater and give you a chance to correct bugs.

6. Each problem must be written up separately. Mark the top of each sheet with the following: (1) your name, (2) the question number, and (3) the names of any people you worked with on the problem ( (only for take-home Quiz-2), or ¡°Collaborators: none¡± if you solved the problem completely alone.

7. No collaboration whatsoever is permitted on in-class quiz or exam.

8. Plagiarism and other dishonest behavior cannot be tolerated in any academic environment that prides itself on individual accomplishment.


University Policies and Regulations

1. Regulations concerning Incomplete Grades: http://academic.fiu.edu/polman/sec16web.htm 

2. For academic misconduct, sexual harassment, religious holydays, and information on services for students with disabilities, please see:

http://www.fiu.edu/provost/polman/sec2/sec2web2-44.htm

http://www.fiu.edu/~eop/EOPSexH.pdf

http://www.fiu.edu/~provost/polman/sec19web.html

©2012 Wei Zeng        http://www.cs.fiu.edu/~wzeng        Last Updated: 11/20/2012