Algorithmic Techniques for Big Data

(Previously numbered CS 369G.) Designing algorithms for efficient processing of large data sets poses unique challenges. This course will discuss algorithmic paradigms that have been developed to efficiently process data sets that are much larger than available memory. We will cover streaming algorithms and sketching methods that produce compact datastructures, dimension reduction methods that preserve geometric structure, efficient algorithms for numerical linear algebra, graph sparsification methods, as well as impossibility results for these techniques.