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BART: Bayesian Additive Regression Trees
We develop a Bayesian "sum-of-trees" model where each tree is constrained by a regularization prior to be a weak learner, and fitting and inference are accomplished via an iterative BayesianExpand
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Bayesian CART Model Search
Abstract In this article we put forward a Bayesian approach for finding classification and regression tree (CART) models. The two basic components of this approach consist of prior specification andExpand
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Bayes and big data: the consensus Monte Carlo algorithm
A useful definition of ‘big data’ is data that is too big to process comfortably on a single machine, either because of processor, memory, or disk bottlenecks. Expand
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Bayesian variable selection with related predictors
  • H. Chipman
  • Computer Science, Mathematics
  • 30 October 1995
This paper develops mathematical representations of this and other relations between predictors, which may then be incorporated in a model selection procedure. Expand
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The Practical Implementation of Bayesian Model Selection
In principle, the Bayesian approach to model selection is straightforward. Expand
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Adaptive Bayesian Wavelet Shrinkage
Abstract When fitting wavelet based models, shrinkage of the empirical wavelet coefficients is an effective tool for denoising the data. This article outlines a Bayesian approach to shrinkage,Expand
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A Bayesian variable-selection approach for analyzing designed experiments with complex aliasing
Experiments using designs with complex aliasing patterns are often performed—for example, twolevel nongeometric Plackett-Burman designs, multilevel and mixed-level fractional factorial designs,Expand
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Interpretable dimension reduction
Abstract The analysis of high-dimensional data often begins with the identification of lower dimensional subspaces. Principal component analysis is a dimension reduction technique that identifiesExpand
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Bayesian Treed Models
We propose a Bayesian approach for finding and fitting parametric treed models, in particular focusing on Bayesian treed regression. Expand
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Bayesian Ensemble Learning
We develop a Bayesian "sum-of-trees" model, named BART, where each tree is constrained by a prior to be a weak learner. Expand
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