Mark Tygert

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 27

Top Topics

Starting Points

Randomized Algorithm

Principal Component Analysis

Top Venues

SIAM J. Matrix Anal. Appl.

Adv. Comput. Math.

Publications

François Charton, Kristin Lauter, Cathy Li, Mark Tygert
An Efficient Algorithm for Integer Lattice Reduction. SIAM J. Matrix Anal. Appl. 45 (1) (2024)
Kamalika Chaudhuri, Chuan Guo, Laurens van der Maaten, Saeed Mahloujifar, Mark Tygert
Guarantees of confidentiality via Hammersley-Chapman-Robbins bounds. CoRR (2024)
Mark Tygert
Calibration of P-values for calibration and for deviation of a subpopulation from the full population. Adv. Comput. Math. 49 (5) (2023)
Isabel M. Kloumann, Hannah Korevaar, Chris McConnell, Mark Tygert, Jessica Zhao
Cumulative differences between paired samples. CoRR (2023)
François Charton, Kristin E. Lauter, Cathy Li, Mark Tygert
An efficient algorithm for integer lattice reduction. CoRR (2023)
Mark Tygert
Calibration of P-values for calibration and for deviation of a subpopulation from the full population. CoRR (2022)
Imanol Arrieta Ibarra, Paman Gujral, Jonathan Tannen, Mark Tygert, Cherie Xu
Metrics of calibration for probabilistic predictions. CoRR (2022)
Aaron Defazio, Mark Tygert, Rachel Ward, Jure Zbontar
Compressed sensing with a jackknife and a bootstrap. J. Data Sci. Stat. Vis. 2 (4) (2022)
Imanol Arrieta Ibarra, Paman Gujral, Jonathan Tannen, Mark Tygert, Cherie Xu
Metrics of Calibration for Probabilistic Predictions. J. Mach. Learn. Res. 23 (2022)
Mark Tygert
A graphical method of cumulative differences between two subpopulations. J. Big Data 8 (1) (2021)
Mark Tygert
Controlling for multiple covariates. CoRR (2021)
Mark Tygert
Cumulative deviation of a subpopulation from the full population. J. Big Data 8 (1) (2021)
Mark Tygert
Cumulative differences between subpopulations. CoRR (2021)
Isabel M. Kloumann, Mark Tygert
An optimizable scalar objective value cannot be objective and should not be the sole objective. CoRR (2020)
Mark Tygert
Plots of the cumulative differences between observed and expected values of ordered Bernoulli variates. CoRR (2020)
Mark Tygert
Plotting the cumulative deviation of a subgroup from the full population as a function of score. CoRR (2020)
Chuan Guo, Awni Y. Hannun, Brian Knott, Laurens van der Maaten, Mark Tygert, Ruiyu Zhu
Secure multiparty computations in floating-point arithmetic. CoRR (2020)
Huamin Li, Yuval Kluger, Mark Tygert
Randomized algorithms for distributed computation of principal component analysis and singular value decomposition. Adv. Comput. Math. 44 (5) (2018)
Mark Tygert, Jure Zbontar
Simulating single-coil MRI from the responses of multiple coils. CoRR (2018)
Mark Tygert
Regression-aware decompositions. CoRR (2017)
Cinna Wu, Mark Tygert, Yann LeCun
Hierarchical loss for classification. CoRR (2017)
Huamin Li, George C. Linderman, Arthur Szlam, Kelly P. Stanton, Yuval Kluger, Mark Tygert
Algorithm 971: An Implementation of a Randomized Algorithm for Principal Component Analysis. ACM Trans. Math. Softw. 43 (3) (2017)
Arthur Szlam, Andrew Tulloch, Mark Tygert
Accurate Low-Rank Approximations Via a Few Iterations of Alternating Least Squares. SIAM J. Matrix Anal. Appl. 38 (2) (2017)
Mark Tygert, Joan Bruna, Soumith Chintala, Yann LeCun, Serkan Piantino, Arthur Szlam
A Mathematical Motivation for Complex-Valued Convolutional Networks. Neural Comput. 28 (5) (2016)
Mark Tygert
Poor starting points in machine learning. CoRR (2016)
Arthur Szlam, Andrew Tulloch, Mark Tygert
Accurate principal component analysis via a few iterations of alternating least squares. CoRR (2016)
Huamin Li, Yuval Kluger, Mark Tygert
Randomized algorithms for distributed computation of principal component analysis and singular value decomposition. CoRR (2016)
Soumith Chintala, Marc'Aurelio Ranzato, Arthur Szlam, Yuandong Tian, Mark Tygert, Wojciech Zaremba
Scale-invariant learning and convolutional networks. CoRR (2015)
Joan Bruna, Soumith Chintala, Yann LeCun, Serkan Piantino, Arthur Szlam, Mark Tygert
A theoretical argument for complex-valued convolutional networks. CoRR (2015)
Arthur Szlam, Yuval Kluger, Mark Tygert
An implementation of a randomized algorithm for principal component analysis. CoRR (2014)
E. S. Coakley, Vladimir Rokhlin, Mark Tygert
A Fast Randomized Algorithm for Orthogonal Projection. SIAM J. Sci. Comput. 33 (2) (2011)
Nathan Halko, Per-Gunnar Martinsson, Yoel Shkolnisky, Mark Tygert
An Algorithm for the Principal Component Analysis of Large Data Sets. SIAM J. Sci. Comput. 33 (5) (2011)
William Perkins, Mark Tygert, Rachel Ward
Computing the confidence levels for a root-mean-square test of goodness-of-fit. Appl. Math. Comput. 217 (22) (2011)
Mark Tygert
Fast algorithms for spherical harmonic expansions, III. J. Comput. Phys. 229 (18) (2010)
Nathan Halko, Per-Gunnar Martinsson, Yoel Shkolnisky, Mark Tygert
An algorithm for the principal component analysis of large data sets CoRR (2010)
Mark Tygert
Fast algorithms for spherical harmonic expansions, III CoRR (2009)
Mark Tygert
A fast algorithm for computing minimal-norm solutions to underdetermined systems of linear equations CoRR (2009)
Vladimir Rokhlin, Mark Tygert
A fast randomized algorithm for orthogonal projection CoRR (2009)
Vladimir Rokhlin, Arthur Szlam, Mark Tygert
A Randomized Algorithm for Principal Component Analysis. SIAM J. Matrix Anal. Appl. 31 (3) (2009)
Mark Tygert
Fast algorithms for spherical harmonic expansions, II. J. Comput. Phys. 227 (8) (2008)
Vladimir Rokhlin, Mark Tygert
Fast Algorithms for Spherical Harmonic Expansions. SIAM J. Sci. Comput. 27 (6) (2006)
Mark Tygert
Recurrence relations and fast algorithms CoRR (2006)