The paper proves polynomial mixing time upper bounds for three data augmentation algorithms (ProbitDA, LogitDA, LassoDA) with explicit dependence on design matrix, prior, n, and d.
Mass transportation and contractions
2 Pith papers cite this work. Polarity classification is still indexing.
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abstract
According to a celebrated result of L. Caffarelli, every optimal mass transportation mapping pushing forward the standard Gaussian measure onto a log-concave measure $e^{-W} dx$ with $D^2 W \ge {Id}$ is 1-Lipschitz. We present a short survey of related results and various applications.
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UNVERDICTED 2representative citing papers
Extends log-Hessian-type bounds on densities to general convex estimates for global derivative bounds on the Brenier map.
citing papers explorer
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Fast Mixing of Data Augmentation Algorithms: Bayesian Probit, Logit, and Lasso Regression
The paper proves polynomial mixing time upper bounds for three data augmentation algorithms (ProbitDA, LogitDA, LassoDA) with explicit dependence on design matrix, prior, n, and d.
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Global estimates on the Brenier map
Extends log-Hessian-type bounds on densities to general convex estimates for global derivative bounds on the Brenier map.