
Classification Trees for Imbalanced and Sparse Data: SurfacetoVolume Regularization
Classification algorithms face difficulties when one or more classes hav...
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Autoencoding graphvalued data with applications to brain connectomes
Our interest focuses on developing statistical methods for analysis of b...
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Nearest Neighbor Dirichlet Process
There is a rich literature on Bayesian nonparametric methods for unknown...
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Lipschitz Bandit Optimization with Improved Efficiency
We consider the Lipschitz bandit optimization problem with an emphasis o...
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Reproducible Bootstrap Aggregating
Heterogeneity between training and testing data degrades reproducibility...
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Classification via local manifold approximation
Classifiers label data as belonging to one of a set of groups based on i...
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Geodesic Distance Estimation with Spherelets
Many statistical and machine learning approaches rely on pairwise distan...
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Bayesian Multi Plate High Throughput Screening of Compounds
High throughput screening of compounds (chemicals) is an essential part ...
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Efficient Manifold and Subspace Approximations with Spherelets
Data lying in a highdimensional ambient space are commonly thought to h...
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Boosting Variational Inference
Variational inference (VI) provides fast approximations of a Bayesian po...
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Variational Gaussian Copula Inference
We utilize copulas to constitute a unified framework for constructing an...
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Probabilistic Curve Learning: Coulomb Repulsion and the Electrostatic Gaussian Process
Learning of low dimensional structure in multidimensional data is a cano...
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Parallelizing MCMC with Random Partition Trees
The modern scale of data has brought new challenges to Bayesian inferenc...
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Locally Adaptive Dynamic Networks
Our focus is on realistically modeling and forecasting dynamic networks ...
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On the consistency theory of high dimensional variable screening
Variable screening is a fast dimension reduction technique for assisting...
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Exploiting Big Data in Logistics Risk Assessment via Bayesian Nonparametrics
In cargo logistics, a key performance measure is transport risk, defined...
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Minimax Optimal Bayesian Aggregation
It is generally believed that ensemble approaches, which combine multipl...
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Bayesian Conditional Density Filtering
We propose a Conditional Density Filtering (CDF) algorithm for efficien...
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Parallelizing MCMC via Weierstrass Sampler
With the rapidly growing scales of statistical problems, subset based co...
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Multiscale Dictionary Learning for Estimating Conditional Distributions
Nonparametric estimation of the conditional distribution of a response g...
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Nonparametric Bayes dynamic modeling of relational data
Symmetric binary matrices representing relations among entities are comm...
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Learning Densities Conditional on Many Interacting Features
Learning a distribution conditional on a set of discretevalued features...
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Bayesian Compressed Regression
As an alternative to variable selection or shrinkage in high dimensional...
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Bayesian Consensus Clustering
The task of clustering a set of objects based on multiple sources of dat...
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Locally adaptive factor processes for multivariate time series
In modeling multivariate time series, it is important to allow timevary...
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Multiresolution Gaussian Processes
We propose a multiresolution Gaussian process to capture longrange, non...
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Bayesian nonparametric multivariate convex regression
In many applications, such as economics, operations research and reinfor...
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Generalized Beta Mixtures of Gaussians
In recent years, a rich variety of shrinkage priors have been proposed t...
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Targeted Random Projection for Prediction from HighDimensional Features
We consider the problem of computationallyefficient prediction from hig...
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Bayesian Constraint Relaxation
Prior information often takes the form of parameter constraints. Bayesia...
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Latent nested nonparametric priors
Discrete random structures are important tools in Bayesian nonparametric...
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Multiresolution Tensor Decomposition for Multiple Spatial Passing Networks
This article is motivated by soccer positional passing networks collecte...
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Bayesian Nonparametric Higher Order Hidden Markov Models
We consider the problem of flexible modeling of higher order hidden Mark...
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Bayesian Distance Clustering
Modelbased clustering is widelyused in a variety of application areas....
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ClusteringEnhanced Stochastic Gradient MCMC for Hidden Markov Models with Rare States
MCMC algorithms for hidden Markov models, which often rely on the forwar...
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Bayesian Modular and Multiscale Regression
We tackle the problem of multiscale regression for predictors that are s...
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Random orthogonal matrices and the Cayley transform
Random orthogonal matrices play an important role in probability and sta...
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Removing the influence of a group variable in highdimensional predictive modelling
Predictive modelling relies on the assumption that observations used for...
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Supervised CoarseGraining of Composite Objects
We consider supervised dimension reduction for regression with composite...
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Constrained Bayesian Inference through Posterior Projections
In a broad variety of settings, prior information takes the form of para...
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Nonparametric graphical model for counts
Although multivariate count data are routinely collected in many applica...
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Multivariate mixed membership modeling: Inferring domainspecific risk profiles
Characterizing shared membership of individuals in two or more categorie...
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Centered Partition Process: Informative Priors for Clustering
There is a very rich literature proposing Bayesian approaches for cluste...
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Bayesian cumulative shrinkage for infinite factorizations
There are a variety of Bayesian models relying on representations in whi...
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Efficient Entropy Estimation for Stationary Time Series
Entropy estimation, due in part to its connection with mutual informatio...
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Bayesian timealigned factor analysis of paired multivariate time series
Many modern data sets require inference methods that can estimate the sh...
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Bayesian Factor Analysis for Inference on Interactions
This article is motivated by the problem of inference on interactions am...
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Bayesian inferences on uncertain ranks and orderings
It is common to be interested in rankings or order relationships among e...
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Estimating densities with nonlinear support using FisherGaussian kernels
Current tools for multivariate density estimation struggle when the dens...
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Monte Carlo simulation on the Stiefel manifold via polar expansion
Motivated by applications to Bayesian inference for statistical models w...
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