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
Latest Publications
Journal of Big Data - November 6, 2021
A graphical method of cumulative differences between two subpopulations
Mark Tygert
Journal of Big Data - July 19, 2021
Cumulative deviation of a subpopulation from the full population
Mark Tygert
Information and Inference: a Journal of the IMA - January 18, 2021
Secure multiparty computations in floating-point arithmetic
Chuan Guo, Awni Hannun, Brian Knott, Laurens van der Maaten, Mark Tygert, Ruiyu Zhu
PLOS ONE - December 3, 2019
A hierarchical loss and its problems when classifying non-hierarchically
Cinna Wu, Mark Tygert, Yann LeCun
SIAM Journal on Matrix Analysis and Applications - December 17, 2018
Regression-aware decompositions
Mark Tygert
ACM 2018 - March 19, 2018
Randomized algorithms for distributed computation of principal component analysis and singular value decomposition
Huamin Li, Yuval Kluger, Mark Tygert
ArXiv - June 25, 2015
Scale-Invariant Learning and Convolutional Networks
Mark Tygert, Arthur Szlam, Soumith Chintala, Marc'Aurelio Ranzato, Yuandong Tian, Wojciech Zaremba
ArXiv - June 22, 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