Dunson, David B.

55 publications

MLJ 2025 Accelerated Algorithms for Convex and Non-Convex Optimization on Manifolds Lizhen Lin, Bayan Saparbayeva, Michael Minyi Zhang, David B. Dunson

JMLR 2024 Spatial Meshing for General Bayesian Multivariate Models Michele Peruzzi, David B. Dunson

JMLR 2023 Bayesian Spanning Tree: Estimating the Backbone of the Dependence Graph Leo L. Duan, David B. Dunson

JMLR 2023 Dimension-Grouped Mixed Membership Models for Multivariate Categorical Data Yuqi Gu, Elena E. Erosheva, Gongjun Xu, David B. Dunson

JMLR 2023 Escaping the Curse of Dimensionality in Bayesian Model-Based Clustering Noirrit Kiran Chandra, Antonio Canale, David B. Dunson

JMLR 2023 Nearest Neighbor Dirichlet Mixtures Shounak Chattopadhyay, Antik Chakraborty, David B. Dunson

JMLR 2022 Spatial Multivariate Trees for Big Data Bayesian Regression Michele Peruzzi, David B. Dunson

JMLR 2021 Bayesian Distance Clustering Leo L. Duan, David B. Dunson

JMLR 2021 Bayesian Time-Aligned Factor Analysis of Paired Multivariate Time Series Arkaprava Roy, Jana Schaich Borg, David B Dunson

JMLR 2021 Soft Tensor Regression Georgia Papadogeorgou, Zhengwu Zhang, David B. Dunson

JMLR 2020 Bayesian Closed Surface Fitting Through Tensor Products Olivier Binette, Debdeep Pati, David B. Dunson

JMLR 2020 Nonparametric Graphical Model for Counts Arkaprava Roy, David B Dunson

JMLR 2018 Scalable Bayes via Barycenter in Wasserstein Space Sanvesh Srivastava, Cheng Li, David B. Dunson

JMLR 2018 Scaling up Data Augmentation MCMC via Calibration Leo L. Duan, James E. Johndrow, David B. Dunson

JMLR 2017 Bayesian Tensor Regression Rajarshi Guhaniyogi, Shaan Qamar, David B. Dunson

JMLR 2017 Robust and Scalable Bayes via a Median of Subset Posterior Measures Stanislav Minsker, Sanvesh Srivastava, Lizhen Lin, David B. Dunson

JMLR 2016 Bayesian Graphical Models for Multivariate Functional Data Hongxiao Zhu, Nate Strawn, David B. Dunson

JMLR 2016 Compressed Gaussian Process for Manifold Regression Rajarshi Guhaniyogi, David B. Dunson

NeurIPS 2016 DECOrrelated Feature Space Partitioning for Distributed Sparse Regression Xiangyu Wang, David B Dunson, Chenlei Leng

AISTATS 2016 Scalable Geometric Density Estimation Ye Wang, Antonio Canale, David B. Dunson

AISTATS 2016 Variational Gaussian Copula Inference Shaobo Han, Xuejun Liao, David B. Dunson, Lawrence Carin

JMLR 2015 Bayesian Nonparametric Covariance Regression Emily B. Fox, David B. Dunson

NeurIPS 2015 On the Consistency Theory of High Dimensional Variable Screening Xiangyu Wang, Chenlei Leng, David B Dunson

NeurIPS 2015 Parallelizing MCMC with Random Partition Trees Xiangyu Wang, Fangjian Guo, Katherine A. Heller, David B Dunson

NeurIPS 2015 Probabilistic Curve Learning: Coulomb Repulsion and the Electrostatic Gaussian Process Ye Wang, David B Dunson

AISTATS 2015 WASP: Scalable Bayes via Barycenters of Subset Posteriors Sanvesh Srivastava, Volkan Cevher, Quoc Tran-Dinh, David B. Dunson

AISTATS 2014 Bayesian Logistic Gaussian Process Models for Dynamic Networks Daniele Durante, David B. Dunson

JMLR 2014 Improving Prediction from Dirichlet Process Mixtures via Enrichment Sara Wade, David B. Dunson, Sonia Petrone, Lorenzo Trippa

JMLR 2014 Locally Adaptive Factor Processes for Multivariate Time Series Daniele Durante, Bruno Scarpa, David B. Dunson

NeurIPS 2014 Median Selection Subset Aggregation for Parallel Inference Xiangyu Wang, Peichao Peng, David B Dunson

AISTATS 2013 Bayesian Learning of Joint Distributions of Objects Anjishnu Banerjee, Jared Murray, David B. Dunson

AISTATS 2013 Diagonal Orthant Multinomial Probit Models James E. Johndrow, David B. Dunson, Kristian Lum

NeurIPS 2013 Locally Adaptive Bayesian Multivariate Time Series Daniele Durante, Bruno Scarpa, David B Dunson

NeurIPS 2013 Multiscale Dictionary Learning for Estimating Conditional Distributions Francesca Petralia, Joshua T Vogelstein, David B Dunson

JMLR 2013 Multivariate Convex Regression with Adaptive Partitioning Lauren A. Hannah, David B. Dunson

ICML 2012 Bayesian Watermark Attacks Ivo Shterev, David B. Dunson

ICML 2012 Ensemble Methods for Convex Regression with Applications to Geometric Programming Based Circuit Design Lauren Hannah, David B. Dunson

ICML 2012 Lognormal and Gamma Mixed Negative Binomial Regression Mingyuan Zhou, Lingbo Li, David B. Dunson, Lawrence Carin

NeurIPS 2012 Multiresolution Gaussian Processes Emily B. Fox, David B. Dunson

NeurIPS 2012 Repulsive Mixtures Francesca Petralia, Vinayak Rao, David B. Dunson

ICML 2011 Approximate Dynamic Programming for Storage Problems Lauren Hannah, David B. Dunson

NeurIPS 2011 Generalized Beta Mixtures of Gaussians Artin Armagan, Merlise Clyde, David B. Dunson

NeurIPS 2011 Hierarchical Topic Modeling for Analysis of Time-Evolving Personal Choices Xianxing Zhang, Lawrence Carin, David B. Dunson

ICML 2011 The Hierarchical Beta Process for Convolutional Factor Analysis and Deep Learning Bo Chen, Gungor Polatkan, Guillermo Sapiro, David B. Dunson, Lawrence Carin

NeurIPS 2011 The Kernel Beta Process Lu Ren, Yingjian Wang, Lawrence Carin, David B. Dunson

ICML 2011 Topic Modeling with Nonparametric Markov Tree Haojun Chen, David B. Dunson, Lawrence Carin

ICML 2011 Tree-Structured Infinite Sparse Factor Model XianXing Zhang, David B. Dunson, Lawrence Carin

JMLR 2010 Classification with Incomplete Data Using Dirichlet Process Priors Chunping Wang, Xuejun Liao, Lawrence Carin, David B. Dunson

NeurIPS 2010 Joint Analysis of Time-Evolving Binary Matrices and Associated Documents Eric Wang, Dehong Liu, Jorge Silva, Lawrence Carin, David B. Dunson

NeurIPS 2009 A Bayesian Model for Simultaneous Image Clustering, Annotation and Object Segmentation Lan Du, Lu Ren, Lawrence Carin, David B. Dunson

ICML 2008 Hierarchical Kernel Stick-Breaking Process for Multi-Task Image Analysis Qi An, Chunping Wang, Ivo Shterev, Eric Wang, Lawrence Carin, David B. Dunson

ICML 2008 Multi-Task Compressive Sensing with Dirichlet Process Priors Yuting Qi, Dehong Liu, David B. Dunson, Lawrence Carin

ICML 2008 The Dynamic Hierarchical Dirichlet Process Lu Ren, David B. Dunson, Lawrence Carin

ICML 2007 Multi-Task Learning for Sequential Data via iHMMs and the Nested Dirichlet Process Kai Ni, Lawrence Carin, David B. Dunson

ICML 2007 The Matrix Stick-Breaking Process for Flexible Multi-Task Learning Ya Xue, David B. Dunson, Lawrence Carin