This course is a first-year graduate course in algorithms. Emphasis is placed on fundamental algorithms and advanced methods of algorithmic design, analysis, and implementation. Techniques to be covered include amortization, randomization, fingerprinting, word-level parallelism, bit scaling, dynamic programming, network flow, linear programming ...

Advanced algorithms build upon basic ones and use new ideas. We will start with networks flows which are used in more typical applications such as optimal matchings, finding disjoint paths and flight scheduling as well as more surprising ones like image segmentation in computer vision.

CS 224 is an advanced course in algorithm design, and topics we will cover include the word RAM model, data structures, amortization, online algorithms, linear programming, semidefinite programming, approximation algorithms, hashing, randomized algorithms, fast exponential time algorithms, graph algorithms, and computational geometry.

The class covers classic and modern algorithmic ideas that are central to many areas of Computer Science. The focus is on most powerful paradigms and techniques of how to design algorithms, and measure their efficiency.

Discover Advanced Algorithms Courses designed to deepen your expertise and mastery in various skills. Enhance your professional capabilities with in-depth knowledge today.

The students in this course were required to take turns scribing lecture notes. They were provided with detailed instructions and a template. The process of scribing lecture notes provides students with valuable experience preparing mathematical documents, and also generates a useful set of lecture notes for the class.

Algorithms for Memory Hierarchies: Advanced Lectures (1st Edition), Lecture Notes in Computer Science, Springer, 2003. Why Parallelism? Unicore Performance Has Hit a Wall! “Everything that can be invented has been invented.” Exhausted all ideas to exploit hidden parallelism? ― So what happens if we overclock by 20%? ― And underclock by 20%?

Gain hands-on experience as you explore foundational concepts, analyze algorithmic complexities, and implement efficient solutions to real-world problems. The journey begins with recursion, where you’ll delve into function control, call stacks, and tree recursion, supplemented by practical examples like factorial computation.

This is a graduate course on the design and analysis of algorithms, covering several advanced topics not studied in typical introductory courses on algorithms.

This course introduces students to advanced techniques for designing and analysing algorithms, and explores their use in a variety of application areas. Prerequisite: One undergraduate course in algorithms, or equivalent mathematical maturity.