[2012 Fall] COT6405U01: Analysis of Algorithms SYLLABUS  SCHEDULE  ANNOUNCEMENTS Conference: GL139, T/R 12:301:45PM Instructor: Dr. Wei Zeng Office: ECS 357 Office Hours: T/R 3:005:30PM Homepage: http://www.cis.fiu.edu/~wzeng/ TA: Rong Rong Email: rrong001@ [Syllabus] Announcements 11/25: Final Exam will be taken at 12:0014:00PM, 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#01Solution has been posted to Moodle! 11/12: Quiz#02 (takehome) 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 12:301:45PM, Oct 09, 2012. 09/23: Assignment#02 has been posted to Moodle! Due date: Sunday 11:59PM, Oct 07, 2012. 09/20: Lectures#0110 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: DivideandConquer, 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, ActivitySelection Problem 10/23: Lecture#18: Amortized Analysis, Table Expansion 10/25: Lecture#19: Linear Programming 10/30: Lecture#20: Advanced Data Structures: BTrees 11/01: Lecture#21: BTrees, 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 MaxFlow 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) DivideandConquer 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, AddisonWesley. 2005. Grading Policy Homework (problem sets / programming): 30% Quiz 1 (inclass): 15% Quiz 2 (takehome): 15% Final Exam (inclass): 35% Participation: 5% Notes: All the homework/Quzi2 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 takehome Quiz2 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 takehome Quiz2), or ¡°Collaborators: none¡± if you solved the problem completely alone. 7. No collaboration whatsoever is permitted on inclass 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/sec2web244.htm 

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