Spring 2022

High-Dimensional Data Analysis

 

Synopsis

Today, machine learning and data science deal with tremendous amounts of high-dimensional data. Processing these data requires extensive computational resources (these often include large CPU and GPU clusters). It is expected that the amount of collected and analyzed data will grow significantly in the coming years. Thus, to advance and broaden the application of data analysis, it is crucial to design new, more efficient algorithms. The special quarter aims to develop new methods and techniques for working with high-dimensional data. We will investigate such topics as dimensionality reduction, sketching, low-distortion embeddings, and streaming. We will organize workshops to bring together researchers from theoretical computer science, machine learning, mathematics, and statistics.

This program is organized by Konstantin Makarychev (NU) and Yury Makarychev (TTIC)

Workshops

Visit the events page to see a full listing of workshops coming up.

Graduate Courses

A graduate-level course on Algorithms for Big Data is offered at Northwestern University.