COT-6405-U01: Analysis of Algorithms
Conference: GL139, T/R 12:30-1:45PM
Instructor: Dr. Wei Zeng
Office: ECS 357
Office Hours: T/R 3:00-5:30PM
TA: Rong Rong
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.
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
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)
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)
[CLRS] Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. Introduction to Algorithms, Third Edition, MIT Press. 2009.
SCIS Graduate Standing, esp., Data Structure, Computer Programming, Algebra, Probability Analysis
Required for MSCS
Elective for MSIT, MSTN, and Ph.D. students
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.
[KT] Kleinberg and Tardos. Algorithm Design, Addison-Wesley. 2005.
Homework (problem sets / programming): 30%
Quiz 1 (in-class): 15%
Quiz 2 (take-home): 15%
Final Exam (in-class): 35%
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:
|©2012 Wei Zeng http://www.cs.fiu.edu/~wzeng Last Updated: 11/20/2012|