
Active multifidelity Bayesian online changepoint detection
Online algorithms for detecting changepoints, or abrupt shifts in the be...
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Contrastive latent variable modeling with application to casecontrol sequencing experiments
Highthroughput RNAsequencing (RNAseq) technologies are powerful tools...
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Latent variable modeling with random features
Gaussian processbased latent variable models are flexible and theoretic...
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Nonparametric Deconvolution Models
We describe nonparametric deconvolution models (NDMs), a family of Bayes...
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Bayesian Ordinal Quantile Regression with a Partially Collapsed Gibbs Sampler
Unlike standard linear regression, quantile regression captures the rela...
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Nonparametric Bayesian multiarmed bandits for single cell experiment design
The problem of maximizing cell type discovery under budget constraints i...
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PatientSpecific Effects of Medication Using Latent Force Models with Gaussian Processes
Multioutput Gaussian processes (GPs) are a flexible Bayesian nonparamet...
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Defining Admissible Rewards for High Confidence Policy Evaluation
A key impediment to reinforcement learning (RL) in real applications wit...
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Sequential Gaussian Processes for Online Learning of Nonstationary Functions
Many machine learning problems can be framed in the context of estimatin...
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An Optimal Policy for Patient Laboratory Tests in Intensive Care Units
Laboratory testing is an integral tool in the management of patient care...
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PGTS: Improved Thompson Sampling for Logistic Contextual Bandits
We address the problem of regret minimization in logistic contextual ban...
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How Algorithmic Confounding in Recommendation Systems Increases Homogeneity and Decreases Utility
Recommendation systems occupy an expanding role in everyday decision mak...
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Large Linear Multioutput Gaussian Process Learning
Gaussian processes (GPs), or distributions over arbitrary functions in a...
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A Reinforcement Learning Approach to Weaning of Mechanical Ventilation in Intensive Care Units
The management of invasive mechanical ventilation, and the regulation of...
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Sparse MultiOutput Gaussian Processes for Medical Time Series Prediction
In realtime monitoring of hospital patients, highquality inference of ...
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Coupled Compound Poisson Factorization
We present a general framework, the coupled compound Poisson factorizati...
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Dynamic Collaborative Filtering with Compound Poisson Factorization
Modelbased collaborative filtering analyzes useritem interactions to i...
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Hierarchical Compound Poisson Factorization
Nonnegative matrix factorization models based on a hierarchical GammaP...
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Unsupervised Domain Adaptation Using Approximate Label Matching
Domain adaptation addresses the problem created when training data is ge...
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Nonparametric ReducedRank Regression for MultiSNP, MultiTrait Association Mapping
Genomewide association studies have proven to be essential for understa...
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Adaptive Randomized Dimension Reduction on Massive Data
The scalability of statistical estimators is of increasing importance in...
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Bayesian group latent factor analysis with structured sparsity
Latent factor models are the canonical statistical tool for exploratory ...
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Differential gene coexpression networks via Bayesian biclustering models
Identifying latent structure in large data matrices is essential for exp...
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