5 papers · 1 filter
Composition as Direction: An Active-Set Ray-Based Model for Sparse High-Dimensional Compositional Data
Michael R Schwob, Jyotishka Datta
[Working Draft] Compositional data are central to microbial, ecological, and environmental research, yet often have four features that are difficult to accommodate jointly: exact z…
Bayesian Global-Local Regularization
Jyotishka Datta, Nick Polson, Vadim Sokolov
We propose a unified framework for global-local regularization that bridges the gap between classical techniques -- such as ridge regression and the nonnegative garotte -- and mode…
Bayesian ICA with super-Gaussian Source Priors
Jyotishka Datta, Soham Ghosh, Nicholas G. Polson
Independent Component Analysis (ICA) plays a central role in modern machine learning as a flexible framework for feature extraction. We introduce a horseshoe-type prior with a late…
Inverse Probability Weighting: from Survey Sampling to Evidence Estimation
Jyotishka Datta, Nicholas Polson
We consider the class of inverse probability weight (IPW) estimators, including the popular Horvitz-Thompson and Hajek estimators used routinely in survey sampling, causal inferenc…
Evidence Estimation in Gaussian Graphical Models Using a Telescoping Block Decomposition of the Precision Matrix
Anindya Bhadra, Ksheera Sagar, David Rowe +2
Marginal likelihood, also known as model evidence, is a fundamental quantity in Bayesian statistics. It is used for model selection using Bayes factors or for empirical Bayes tunin…