Mark Tygert

Adv. Comput. Math., October, 2023

Cumulative differences between paired samples.

[BibT_eX]

[DOI]

CoRR, 2023

2022

Metrics of Calibration for Probabilistic Predictions.

[BibT_eX]

[DOI]

Imanol Arrieta Ibarra

J. Mach. Learn. Res., 2022

Compressed sensing with a jackknife and a bootstrap.

[BibT_eX]

[DOI]

J. Data Sci. Stat. Vis., 2022

2021

A graphical method of cumulative differences between two subpopulations.

[BibT_eX]

[DOI]

J. Big Data, 2021

Cumulative deviation of a subpopulation from the full population.

[BibT_eX]

[DOI]

J. Big Data, 2021

Controlling for multiple covariates.

[BibT_eX]

[DOI]

CoRR, 2021

Cumulative differences between subpopulations.

[BibT_eX]

[DOI]

CoRR, 2021

2020

Plotting the cumulative deviation of a subgroup from the full population as a function of score.

[BibT_eX]

[DOI]

CoRR, 2020

An optimizable scalar objective value cannot be objective and should not be the sole objective.

[BibT_eX]

[DOI]

Isabel M. Kloumann

CoRR, 2020

Plots of the cumulative differences between observed and expected values of ordered Bernoulli variates.

[BibT_eX]

[DOI]

CoRR, 2020

Secure multiparty computations in floating-point arithmetic.

[BibT_eX]

[DOI]

Chuan Guo

Awni Y. Hannun

Brian Knott

Laurens van der Maaten

Ruiyu Zhu

CoRR, 2020

2018

Simulating single-coil MRI from the responses of multiple coils.

[BibT_eX]

[DOI]

Jure Zbontar

CoRR, 2018

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

[BibT_eX]

[DOI]

Huamin Li

Yuval Kluger

Adv. Comput. Math., 2018

2017

Algorithm 971: An Implementation of a Randomized Algorithm for Principal Component Analysis.

[BibT_eX]

[DOI]

ACM Trans. Math. Softw., 2017

Accurate Low-Rank Approximations Via a Few Iterations of Alternating Least Squares.

[BibT_eX]

[DOI]

Andrew Tulloch

SIAM J. Matrix Anal. Appl., 2017

Regression-aware decompositions.

[BibT_eX]

[DOI]

CoRR, 2017

Hierarchical loss for classification.

[BibT_eX]

[DOI]

Cinna Wu

Yann LeCun

CoRR, 2017

2016

A Mathematical Motivation for Complex-Valued Convolutional Networks.

[BibT_eX]

[DOI]

Neural Comput., 2016

Poor starting points in machine learning.

[BibT_eX]

[DOI]

CoRR, 2016

Accurate principal component analysis via a few iterations of alternating least squares.

[BibT_eX]

[DOI]

Andrew Tulloch

CoRR, 2016

2015

Scale-invariant learning and convolutional networks.

[BibT_eX]

[DOI]

CoRR, 2015

A theoretical argument for complex-valued convolutional networks.

[BibT_eX]

[DOI]

CoRR, 2015

2014

An implementation of a randomized algorithm for principal component analysis.

[BibT_eX]

[DOI]

Yuval Kluger

CoRR, 2014

2011

An Algorithm for the Principal Component Analysis of Large Data Sets.

[BibT_eX]

[DOI]

Nathan Halko

Per-Gunnar Martinsson

Yoel Shkolnisky

SIAM J. Sci. Comput., 2011

A Fast Randomized Algorithm for Orthogonal Projection.

[BibT_eX]

[DOI]

E. S. Coakley

SIAM J. Sci. Comput., 2011

Computing the confidence levels for a root-mean-square test of goodness-of-fit.

[BibT_eX]

[DOI]

William Perkins

Rachel A. Ward

Appl. Math. Comput., 2011

2010

Fast algorithms for spherical harmonic expansions, III.

[BibT_eX]

[DOI]

J. Comput. Phys., 2010

2009

A Randomized Algorithm for Principal Component Analysis.

[BibT_eX]

[DOI]

SIAM J. Matrix Anal. Appl., 2009

A fast randomized algorithm for orthogonal projection

[BibT_eX]

[DOI]

CoRR, 2009

A fast algorithm for computing minimal-norm solutions to underdetermined systems of linear equations

[BibT_eX]

[DOI]

CoRR, 2009

2008

Fast algorithms for spherical harmonic expansions, II.

[BibT_eX]

[DOI]

J. Comput. Phys., 2008

2006

Fast Algorithms for Spherical Harmonic Expansions.

[BibT_eX]

[DOI]

SIAM J. Sci. Comput., 2006

Recurrence relations and fast algorithms

[BibT_eX]

[DOI]