Recurrence relations and fast algorithms - Mark Tygert (CoRR, 2006)

Fast Algorithms for Spherical Harmonic Expansions. - Vladimir Rokhlin; Mark Tygert (SIAM J. Sci. Comput., 2006)

Fast algorithms for spherical harmonic expansions, II. - Mark Tygert (J. Comput. Phys., 2008)

A fast algorithm for computing minimal-norm solutions to underdetermined systems of linear equations - Mark Tygert (CoRR, 2009)

A fast randomized algorithm for orthogonal projection - Vladimir Rokhlin; Mark Tygert (CoRR, 2009)

A Randomized Algorithm for Principal Component Analysis. - Vladimir Rokhlin; Arthur Szlam; Mark Tygert (SIAM J. Matrix Anal. Appl., 2009)

Fast algorithms for spherical harmonic expansions, III. - Mark Tygert (J. Comput. Phys., 2010)

Computing the confidence levels for a root-mean-square test of goodness-of-fit. - William Perkins 001; Mark Tygert; Rachel A. Ward (Appl. Math. Comput., 2011)

A Fast Randomized Algorithm for Orthogonal Projection. - E. S. Coakley; Vladimir Rokhlin; Mark Tygert (SIAM J. Sci. Comput., 2011)

An Algorithm for the Principal Component Analysis of Large Data Sets. - Nathan Halko; Per-Gunnar Martinsson; Yoel Shkolnisky; Mark Tygert (SIAM J. Sci. Comput., 2011)

An implementation of a randomized algorithm for principal component analysis. - Arthur Szlam; Yuval Kluger; Mark Tygert (CoRR, 2014)

A theoretical argument for complex-valued convolutional networks. - Joan Bruna; Soumith Chintala; Yann LeCun; Serkan Piantino; Arthur Szlam; Mark Tygert (CoRR, 2015)

Scale-invariant learning and convolutional networks. - Soumith Chintala; Marc'Aurelio Ranzato; Arthur Szlam; Yuandong Tian; Mark Tygert; Wojciech Zaremba (CoRR, 2015)

Accurate principal component analysis via a few iterations of alternating least squares. - Arthur Szlam; Andrew Tulloch; Mark Tygert (CoRR, 2016)

Poor starting points in machine learning. - Mark Tygert (CoRR, 2016)

A Mathematical Motivation for Complex-Valued Convolutional Networks. - Mark Tygert; Joan Bruna; Soumith Chintala; Yann LeCun; Serkan Piantino; Arthur Szlam (Neural Comput., 2016)

Hierarchical loss for classification. - Cinna Wu; Mark Tygert; Yann LeCun (CoRR, 2017)

Regression-aware decompositions. - Mark Tygert (CoRR, 2017)

Accurate Low-Rank Approximations Via a Few Iterations of Alternating Least Squares. - Arthur Szlam; Andrew Tulloch; Mark Tygert (SIAM J. Matrix Anal. Appl., 2017)

Algorithm 971: An Implementation of a Randomized Algorithm for Principal Component Analysis. - Huamin Li; George C. Linderman; Arthur Szlam; Kelly P. Stanton; Yuval Kluger; Mark Tygert (ACM Trans. Math. Softw., 2017)

Randomized algorithms for distributed computation of principal component analysis and singular value decomposition. - Huamin Li; Yuval Kluger; Mark Tygert (Adv. Comput. Math., 2018)

Simulating single-coil MRI from the responses of multiple coils. - Mark Tygert; Jure Zbontar (CoRR, 2018)

Secure multiparty computations in floating-point arithmetic. - Chuan Guo 001; Awni Y. Hannun; Brian Knott; Laurens van der Maaten; Mark Tygert; Ruiyu Zhu (CoRR, 2020)

Plots of the cumulative differences between observed and expected values of ordered Bernoulli variates. - Mark Tygert (CoRR, 2020)

An optimizable scalar objective value cannot be objective and should not be the sole objective. - Isabel M. Kloumann; Mark Tygert (CoRR, 2020)

Plotting the cumulative deviation of a subgroup from the full population as a function of score. - Mark Tygert (CoRR, 2020)

Cumulative differences between subpopulations. - Mark Tygert (CoRR, 2021)

Controlling for multiple covariates. - Mark Tygert (CoRR, 2021)

Cumulative deviation of a subpopulation from the full population. - Mark Tygert (J. Big Data, 2021)

A graphical method of cumulative differences between two subpopulations. - Mark Tygert (J. Big Data, 2021)

Compressed sensing with a jackknife and a bootstrap. - Aaron Defazio; Mark Tygert; Rachel A. Ward; Jure Zbontar (J. Data Sci. Stat. Vis., 2022)

Metrics of Calibration for Probabilistic Predictions. - Imanol Arrieta Ibarra; Paman Gujral; Jonathan Tannen; Mark Tygert; Cherie Xu (J. Mach. Learn. Res., 2022)

Cumulative differences between paired samples. - Isabel M. Kloumann; Hannah Korevaar; Chris McConnell; Mark Tygert; Jessica Zhao (CoRR, 2023)

Calibration of P-values for calibration and for deviation of a subpopulation from the full population. - Mark Tygert (Adv. Comput. Math., 2023)

Guarantees of confidentiality via Hammersley-Chapman-Robbins bounds. - Kamalika Chaudhuri; Chuan Guo 001; Laurens van der Maaten; Saeed Mahloujifar; Mark Tygert (Trans. Mach. Learn. Res., 2024)

An Efficient Algorithm for Integer Lattice Reduction. - François Charton; Kristin E. Lauter; Cathy Yuanchen Li; Mark Tygert (SIAM J. Matrix Anal. Appl., 2024)

Measuring multi-calibration. - Ido Guy; Daniel Haimovich; Fridolin Linder; Nastaran Okati; Lorenzo Perini; Niek Tax; Mark Tygert (CoRR, 2025)