Mark Tygert

Research Scientist

Facebook AI Research

Positions prior to Facebook Artificial Intelligence Research were on the faculty at NYU’s Courant Institute, UCLA, and Yale, following undergraduate, graduate, and postdoctoral studies at Princeton and Yale. Research focuses have included fast spherical harmonic transforms, randomized algorithms for linear algebra, and complements to chi-square tests. Recent honors include the 2010 William O. Baker Award from the U.S. National Academy of Sciences and a 2012 DARPA Young Faculty Award.

Interests

Computational science and statistics

Website
Google Scholar Profile
Website
Google Scholar Profile

Latest Publications

Regression-aware decompositions

Mark Tygert

SIAM Journal on Matrix Analysis and Applications - December 17, 2018

Randomized algorithms for distributed computation of principal component analysis and singular value decomposition

Huamin Li, Yuval Kluger, Mark Tygert

ACM 2018 - March 19, 2018

Scale-Invariant Learning and Convolutional Networks

Mark Tygert, Arthur Szlam, Soumith Chintala, Marc'Aurelio Ranzato, Yuandong Tian, Wojciech Zaremba

ArXiv - June 25, 2015

A Theoretical Argument for Complex-Valued Convolutional Networks

Joan Bruna, Soumith Chintala, Yann LeCun, Serkan Piantino, Arthur Szlam, Mark Tygert

ArXiv - June 22, 2015

An Implementation of a Randomized Algorithm for Principal Component Analysis

Arthur Szlam, Mark Tygert, Yuval Kluger

ArXiv - June 22, 2015