Consensus Monte Carlo for Random Subsets Using Shared Anchors
We present a consensus Monte Carlo algorithm that scales existing Bayesian nonparametric models for clustering and feature allocation to big data. The algorithm is valid for any prior on random sub…
Scalable Bayesian Nonparametric Clustering and Classification
We develop a scalable multistep Monte Carlo algorithm for inference under a large class of nonparametric Bayesian models for clustering and classification. Each step is “embarrassingly parallel�…
A Semiparametric Bayesian Approach to Dropout in Longitudinal Studies With Au…
We develop a semiparametric Bayesian approach to missing outcome data in longitudinal studies in the presence of auxiliary covariates. We consider a joint model for the full data response, missingn…
A Product Partition Model With Regression on Covariates
We propose a probability model for random partitions in the presence of covariates. In other words, we develop a model-based clustering algorithm that exploits available covariates. The motivating …
A Nonparametric Approach to Detect Nonlinear Correlation in Gene Expression
We propose a distribution-free approach to detect nonlinear relationships by reporting local correlation. The effect of our proposed method is analogous to piecewise linear approximation although t…
The Shadow Prior
In this article we consider posterior simulation in models with constrained parameter or sampling spaces. Constraints on the support of sampling and prior distributions give rise to a normalization…
Bayesian Nonparametric Common Atoms Regression for Generating Synthetic Contr…
The availability of electronic health records (EHR) has opened opportunities to supplement increasingly expensive and difficult to carry out randomized controlled trials (RCT) with evidence from re…
Search Algorithms and Loss Functions for Bayesian Clustering
We propose a randomized greedy search algorithm to find a point estimate for a random partition based on a loss function and posterior Monte Carlo samples. Given the large size and awkward discrete…
Clustering and Prediction With Variable Dimension Covariates
In many applied fields incomplete covariate vectors are commonly encountered. It is well known that this can be problematic when making inference on model parameters, but its impact on prediction p…
Single-Frequency 336 W Spliceless All-Fiber Amplifier Based on a Chirally-Cou…
Specialty fibers such as chirally-coupled-core fibers show a high potential for further power scaling of single-frequency fiber amplifiers. For the first time, we demonstrate a spliceless all-fiber…
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