CMPS 6610/4610 Algorithms
Fall 18

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Course Description:

This course is a graduate introduction to the design and analysis of algorithms, and covers several basic algorithmic paradigms and their application to core computational problems in graph theory and optimization, as well as analysis of time and space complexity. The primary focus of the course will be on understanding the divide-and-conquer, greedy and dynamic programming paradigms for algorithm design as well as the problem areas to which they can be applied. We will also cover selected advanced techniques in algorithms and their use in a variety of now-classic results in the design and analysis of algorithms. Example application areas include graph theory, discrete optimization, numeric and scientific computing and machine learning. We will cover the following topics in this course:

Asymptotic Analysis and Big-O Notation
Divide-and-Conquer Algorithms
Recurrences and The Master Method
Greedy Algorithms
Randomized Algorithms
Graph Algorithms (Breadth-First Search, Depth-First Search, Connectivity and Shortest Paths)
Dynamic Programming
Lower Bounds, Computational Complexity, and Approximation Algorithms

At the end of this course, students will have a technical understanding of a variety of algorithmic paradigms as well as their applications in practice.

There will be weekly written homework assignments. Undergraduate students will receive different sets of homework assignments and exams.

Please visit the resources page for links to the class schedule, demos and other relevant resources.

Prerequisites:

The equivalent of CMPS/MATH 2170 Discrete Mathematics and CMPS 2200 Introduction to Algorithms, or consent of the instructor. Please do not hesitate to contact the instructor at cwenk -at- tulane -dot- edu if you have questions.

Class Webpage:

http://www.cs.tulane.edu/~carola/teaching/cmps6610/fall18/

Time & Place:

Mondays, Wednesdays, Fridays 2pm - 2:50pm, Gibson 325

Textbooks:

Required: Introduction to Algorithms, 3rd Edition; Cormen, Leiserson, Rivest, and Stein; MIT Press.

Additional materials (research papers, etc) will be provided as necessary.

Optional references:
Algorithms by Dasgupta, Papadimitriou, Vazirani
Algorithm Design by Kleinberg and Tardos

Instructor:

Carola Wenk
Stanley Thomas, 303F
E-mail: cwenk -at- tulane -dot- edu
Phone: 504-865-5805
Office hours: W 3:15pm-4:15pm, F 3pm-4pm, and by appointment

Last modified by Carola Wenk, cwenk -at- tulane -dot- edu,