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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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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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05/13/2023
An Active Learning-based Approach for Hosting Capacity Analysis in Distribution Systems
With the increasing amount of distributed energy resources (DERs) integr...
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04/29/2023
EBLIME: Enhanced Bayesian Local Interpretable Model-agnostic Explanations
We propose EBLIME to explain black-box machine learning models and obtai...
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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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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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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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12/14/2020
Approximate Laplace approximations for scalable model selection
We propose the approximate Laplace approximation (ALA) to evaluate integ...
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12/09/2020
Coupled Markov chain Monte Carlo for high-dimensional regression with Half-t priors
Continuous shrinkage priors are commonly used in Bayesian analysis of hi...
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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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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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02/17/2020
Nonparametric Bayesian Deconvolution of a Symmetric Unimodal Density
We consider nonparametric measurement error density deconvolution subjec...
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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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07/02/2019
Bandit Learning Through Biased Maximum Likelihood Estimation
We propose BMLE, a new family of bandit algorithms, that are formulated ...
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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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11/20/2018
Higher significance with smaller samples: A modified Sequential Probability Ratio Test
We describe a modified sequential probability ratio test that can be use...
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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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10/29/2018
Heteroscedastic Bandits with Reneging
Although shown to be useful in many areas as models for solving sequenti...
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10/21/2018
Signal Adaptive Variable Selector for the Horseshoe Prior
In this article, we propose a simple method to perform variable selectio...
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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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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