5134 Upson. 255-3600.

Overview

CS 683 is a new course designed to serve as an advanced follow-up to CS 681. The goal is to cover recent results and current problems, and illustrate a number of open directions of research in algorithms. The course pre-requisite is CS 681 or equivalent background in algorithms and discrete mathematics.

The course focuses on an inter-related collection of topics centered around randomization, graph decomposition, and methods from high-dimensional geometry. It concentrates on both fundamental techniques and their applications. Techniques include linear programming duality, metric embeddings, random walks, random sampling, spectral partitioning, and spectral clustering. Applications include graph partitioning and its role in approximation algorithms; heuristics for routing; approximate sampling and counting; and high-dimensional clustering and indexing.

Course Outline

(1) Brief introduction to linear programming and duality.