Algebraic Fundamentals of Representing Data
APMTH 210
Subject & Catalog Number
Course Information
Description
Algebra gives mathematical abstractions that allow us to process information. Many optimization problems in data and learning are built on algebraic ideas. For example, principal component analysis finds a low rank approximation of a matrix, a problem central to linear algebra. This course builds out from this example to study the algebraic fundamentals of optimization problems to find representations of data. The course combines mathematical theory, computational experiments, and exploration of data. The focus is on current research developments and connections to open problems. By the end, students will have a unified algebraic toolbox to understand existing methods, to design new models, and to prove results on their theoretical underpinnings.
Available for Harvard Cross Registration
