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Regularization Paths for Generalized Linear Models via Coordinate Descent.
TLDR
We develop fast algorithms for estimation of generalized linear models with convex penalties. Expand
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Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent.
TLDR
We introduce a pathwise algorithm for the Cox proportional hazards model, regularized by convex combinations of ℓ1 and ™2 penalties (elastic net). Expand
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Extracting binary signals from microarray time-course data
This article presents a new method for analyzing microarray time courses by identifying genes that undergo abrupt transitions in expression level, and the time at which the transitions occur. TheExpand
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Regularization Paths for Conditional Logistic Regression: The clogitL1 Package.
We apply the cyclic coordinate descent algorithm of Friedman, Hastie, and Tibshirani (2010) to the fitting of a conditional logistic regression model with lasso [Formula: see text] and elastic netExpand
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�-norm Support Vector Machines
The standard -norm SVM is known for its goodperformancein twoclassclassification. In this paper , we considerthe -norm SVM. We arguethatthe -normSVM mayhavesomeadvantageover thestandard -norm SVM,Expand
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Results from the second year of a collaborative effort to forecast influenza seasons in the United States.
Accurate forecasts could enable more informed public health decisions. Since 2013, CDC has worked with external researchers to improve influenza forecasts by coordinating seasonal challenges for theExpand
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Regularization methods for learning incomplete matrices
AbstractWe use convex relaxation techniques to provide a sequence of solutions to the matrix completionproblem. Using the nuclear norm as a regularizer, we provide simple and very efficient algorithmsExpand
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A pliable lasso for the Cox model
We introduce a pliable lasso method for estimation of interaction effects in the Cox proportional hazards model framework. The pliable lasso is a linear model that includes interactions betweenExpand
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Discriminant Analysis with Adaptively Pooled Covariance
Linear and Quadratic Discriminant analysis (LDA/QDA) are common tools for classification problems. For these methods we assume observations are normally distributed within group. We estimate a meanExpand
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Modeling COVID19 mortality in the US: Community context and mobility matter
The United States has become an epicenter for the coronavirus disease 2019 (COVID-19) pandemic. However, communities have been unequally affected and evidence is growing that social determinants ofExpand
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