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Michal Pilipczuk: Introduction to Parameterized Algorithms, Lecture II

Offered By: Hausdorff Center for Mathematics via YouTube

Tags

Algorithm Design Courses Linear Programming Courses Dynamic programming Courses Discrete Optimization Courses Parameterized Complexity Courses

Course Description

Overview

Dive into the second lecture of a mini-course on parameterized complexity, focusing on methods related to linear programming in algorithmic design. Explore advanced techniques for developing parameterized algorithms, including branching, color coding, kernelization, and width-based dynamic programming. Progress to discrete optimization problems, examining LP-guided branching and kernelization, Lenstra's algorithm for integer linear programming in fixed dimension, and methods for solving structured ILPs using Graver bases. Gain a deeper understanding of these sophisticated approaches in the field of parameterized algorithms during this 1-hour and 9-minute lecture presented by Michal Pilipczuk at the Hausdorff Center for Mathematics.

Syllabus

Michal Pilipczuk: Introduction to parameterized algorithms, lecture II


Taught by

Hausdorff Center for Mathematics

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