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09/12/2023
Generalized Regret Analysis of Thompson Sampling using Fractional Posteriors
Thompson sampling (TS) is one of the most popular and earliest algorithm...
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08/15/2023
Covariate-Assisted Bayesian Graph Learning for Heterogeneous Data
In a traditional Gaussian graphical model, data homogeneity is routinely...
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07/19/2023
Memory Efficient And Minimax Distribution Estimation Under Wasserstein Distance Using Bayesian Histograms
We study Bayesian histograms for distribution estimation on [0,1]^d unde...
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06/01/2023
On the Convergence of Coordinate Ascent Variational Inference
As a computational alternative to Markov chain Monte Carlo approaches, v...
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05/27/2023
Fair Clustering via Hierarchical Fair-Dirichlet Process
The advent of ML-driven decision-making and policy formation has led to ...
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04/19/2023
Blocked Gibbs sampler for hierarchical Dirichlet processes
Posterior computation in hierarchical Dirichlet process (HDP) mixture mo...
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03/17/2023
Robust probabilistic inference via a constrained transport metric
Flexible Bayesian models are typically constructed using limits of large...
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03/15/2023
An Approximate Bayesian Approach to Covariate-dependent Graphical Modeling
Gaussian graphical models typically assume a homogeneous structure acros...
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09/30/2022
Factorized Fusion Shrinkage for Dynamic Relational Data
Modern data science applications often involve complex relational data w...
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09/29/2022
Structured Optimal Variational Inference for Dynamic Latent Space Models
We consider a latent space model for dynamic networks, where our objecti...
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12/18/2021
Off-Policy Evaluation Using Information Borrowing and Context-Based Switching
We consider the off-policy evaluation (OPE) problem in contextual bandit...
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03/15/2021
Adaptive posterior convergence in sparse high dimensional clipped generalized linear models
We develop a framework to study posterior contraction rates in sparse hi...
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02/24/2021
A Hybrid Approximation to the Marginal Likelihood
Computing the marginal likelihood or evidence is one of the core challen...
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10/25/2020
Statistical optimality and stability of tangent transform algorithms in logit models
A systematic approach to finding variational approximation in an otherwi...
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10/23/2020
Statistical Guarantees for Transformation Based Models with Applications to Implicit Variational Inference
Transformation-based methods have been an attractive approach in non-par...
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10/19/2020
Statistical Guarantees and Algorithmic Convergence Issues of Variational Boosting
We provide statistical guarantees for Bayesian variational boosting by p...
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08/11/2020
Evidence bounds in singular models: probabilistic and variational perspectives
The marginal likelihood or evidence in Bayesian statistics contains an i...
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07/13/2020
Dynamics of coordinate ascent variational inference: A case study in 2D Ising models
Variational algorithms have gained prominence over the past two decades ...
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07/04/2020
Continuous shrinkage prior revisited: a collapsing behavior and remedy
Modern genomic studies are increasingly focused on identifying more and ...
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05/16/2020
Nonasymptotic Laplace approximation under model misspecification
We present non-asymptotic two-sided bounds to the log-marginal likelihoo...
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01/26/2020
On truncated multivariate normal priors in constrained parameter spaces
We show that any lower-dimensional marginal density obtained from trunca...
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12/11/2019
Bayesian Copula Density Deconvolution for Zero-Inflated Data in Nutritional Epidemiology
Estimating the marginal and joint densities of the long-term average int...
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10/14/2019
Gaussian Processes with Errors in Variables: Theory and Computation
Covariate measurement error in nonparametric regression is a common prob...
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02/13/2019
Efficient Bayesian shape-restricted function estimation with constrained Gaussian process priors
This article revisits the problem of Bayesian shape-restricted inference...
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01/14/2019
Bayesian Graph Selection Consistency For Decomposable Graphs
Gaussian graphical models are a popular tool to learn the dependence str...
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11/02/2018
Bayesian Hierarchical Modeling on Covariance Valued Data
Analysis of structural and functional connectivity (FC) of human brains ...
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08/17/2018
Revisiting the proton-radius problem using constrained Gaussian processes
Background: The "proton radius puzzle" refers to an eight-year old probl...
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07/24/2018
The Soft Multivariate Truncated Normal Distribution
We propose a new distribution, called the soft tMVN distribution, which ...
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04/04/2018
Shape-Constrained Univariate Density Estimation
While the problem of estimating a probability density function (pdf) fro...
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12/25/2017
On Statistical Optimality of Variational Bayes
The article addresses a long-standing open problem on the justification ...
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10/09/2017
α-Variational Inference with Statistical Guarantees
We propose a variational approximation to Bayesian posterior distributio...
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08/16/2017
Frequentist coverage and sup-norm convergence rate in Gaussian process regression
Gaussian process (GP) regression is a powerful interpolation technique d...
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01/02/2017
Bayesian model selection consistency and oracle inequality with intractable marginal likelihood
In this article, we investigate large sample properties of model selecti...
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07/09/2016
Sparse additive Gaussian process with soft interactions
Additive nonparametric regression models provide an attractive tool for ...
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04/01/2015
