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.
Time & Place:
Tuesdays, Thursdays 2:05pm - 3:15pm, outdoors
(backup classroom BO 240)
Textbooks:
All textbooks are optional.
- CLRS book: Introduction to Algorithms, 3rd Edition; Cormen, Leiserson, Rivest, and Stein; MIT Press.
- Algorithm Design by Kleinberg and Tardos
- Algorithms by Dasgupta, Papadimitriou, Vazirani
- Additional materials (research papers, etc) will be provided as necessary.
Instructor:
Carola Wenk
Stanley Thomas, 303F
E-mail: cwenk -at- tulane -dot- edu
Phone: 504-865-5805
Office hours: Mondays 1pm-2pm, Wednesdays 4pm-5pm, and by appointment.
Please reserve an office hour slot
before coming to office hours.
Last modified by Carola Wenk,
cwenk -at- tulane -dot- edu,