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05/18/2023
Cumulative differences between paired samples
The simplest, most common paired samples consist of observations from tw...
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03/03/2023
An efficient algorithm for integer lattice reduction
A lattice of integers is the collection of all linear combinations of a ...
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07/27/2022
Ties in ranking scores can be treated as weighted samples
Prior proposals for cumulative statistics suggest making tiny random per...
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05/19/2022
Metrics of calibration for probabilistic predictions
Predictions are often probabilities; e.g., a prediction could be for pre...
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01/31/2022
Calibration of P-values for calibration and for deviation of a subpopulation from the full population
The author's recent research papers, "Cumulative deviation of a subpopul...
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12/01/2021
Controlling for multiple covariates
A fundamental problem in statistics is to compare the outcomes attained ...
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08/05/2021
Cumulative differences between subpopulations
Comparing the differences in outcomes (that is, in "dependent variables"...
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08/04/2020
Plotting the cumulative deviation of a subgroup from the full population as a function of score
Assessing whether a subgroup of a full population is getting treated equ...
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06/03/2020
An optimizable scalar objective value cannot be objective and should not be the sole objective
This paper concerns the ethics and morality of algorithms and computatio...
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06/03/2020
Plots of the cumulative differences between observed and expected values of ordered Bernoulli variates
Many predictions are probabilistic in nature; for example, a prediction ...
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01/09/2020
Secure multiparty computations in floating-point arithmetic
Secure multiparty computations enable the distribution of so-called shar...
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02/02/2019
Methods of interpreting error estimates for grayscale image reconstructions
One representation of possible errors in a grayscale image reconstructio...
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11/19/2018
Simulating single-coil MRI from the responses of multiple coils
We convert the information-rich measurements of parallel and phased-arra...
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09/18/2018
Compressed sensing with a jackknife and a bootstrap
Compressed sensing proposes to reconstruct more degrees of freedom in a ...
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09/01/2017
Hierarchical loss for classification
Failing to distinguish between a sheepdog and a skyscraper should be wor...
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02/09/2016
Poor starting points in machine learning
Poor (even random) starting points for learning/training/optimization ar...
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06/26/2015
Convolutional networks and learning invariant to homogeneous multiplicative scalings
The conventional classification schemes -- notably multinomial logistic ...
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03/11/2015