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COMP_SCI 496: Algorithms for Big Data

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Prerequisites

PhD students or Permission of Instructor

Description

This is a graduate-level course on theoretical aspects of Big Data. We will examine algorithms and data structures for dealing with massive data sets. We will discuss such topics as streaming algorithms, sublinear algorithms, dynamic graph algorithms, dimensionality reduction, metric embeddings, sketching, and parallel algorithms. In this course, students will read and present papers on the cutting-edge research in the area of Big Data.

REFERENCE TEXTBOOKS: N/A
REQUIRED TEXTBOOK: N/A

COURSE COORDINATORS: Katherine Compton

COURSE INSTRUCTOR : Prof. Konstantin Makarychev