The MIT professor and Junior Fellow at Harvard sat down with Fifteen Minutes to discuss numerical analysis, CTE, and his favorite NFL team.

Our analysis builds upon two simple structural conditions that boil down to randomized matrix multiplication, a fundamental and well-understood primitive of randomized numerical linear algebra.

In the past few decades, multi-linear algebra also known as tensor algebra has been adapted and employed as a tool for various engineering applications. Recent developments in tensor algebra have ...

We present and analyze three randomized algorithms to approximate von Neumann entropy of real density matrices: our algorithms leverage recent developments in the Randomized Numerical Linear Algebra ...

This book was conceived as a text combining the course of linear algebra and analytic geometry. It originated as a course of lectures delivered by N. V. Efimov at Moscow State University (mechanics ...

Our main result solves this open problem by exploiting the hierarchical structure of G (9) and randomized linear algebra techniques (10, 13). We derive a randomized algorithm that provably succeeds ...

Singular value decomposition (SVD) is a key step in many algorithms in statistics, machine learning and numerical linear algebra. While classical singular value decomposition has been made efficient ...