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Accelerated Algorithms for Convex and Non-Convex Optimization on Manifolds


Oct 18, 2020
Lizhen Lin, Bayan Saparbayeva, Michael Minyi Zhang, David B. Dunson


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Extended Stochastic Block Models


Jul 16, 2020
Sirio Legramanti, Tommaso Rigon, Daniele Durante, David B. Dunson


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A generalized Bayes framework for probabilistic clustering


Jun 09, 2020
Tommaso Rigon, Amy H. Herring, David B. Dunson


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Classification Trees for Imbalanced and Sparse Data: Surface-to-Volume Regularization


Apr 26, 2020
Yichen Zhu, David B. Dunson

* Submitted to Journal of American Statistical Association 

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Nearest Neighbor Dirichlet Process


Mar 17, 2020
Shounak Chattopadhyay, Antik Chakraborty, David B. Dunson


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Reproducible Bootstrap Aggregating


Jan 12, 2020
Meimei Liu, David B. Dunson


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Auto-encoding graph-valued data with applications to brain connectomes


Nov 07, 2019
Meimei Liu, Zhengwu Zhang, David B. Dunson

* 31 pages, 12 figures, 5 tables 

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Lipschitz Bandit Optimization with Improved Efficiency


May 15, 2019
Xu Zhu, David B. Dunson

* The papers have been removed and we refer the readers to arXiv:1901.09277 

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Supervised Coarse-Graining of Composite Objects


Jan 01, 2019
Shaobo Han, David B. Dunson

* 34 pages, 11 figures 

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Efficient Manifold and Subspace Approximations with Spherelets


Jul 30, 2018
Didong Li, Minerva Mukhopadhyay, David B. Dunson


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Multiresolution Tensor Decomposition for Multiple Spatial Passing Networks


Mar 03, 2018
Shaobo Han, David B. Dunson

* 34 pages, 15 figures 

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Bayesian Multi Plate High Throughput Screening of Compounds


Sep 28, 2017
Ivo D. Shterev, David B. Dunson, Cliburn Chan, Gregory D. Sempowski


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Boosting Variational Inference


Mar 01, 2017
Fangjian Guo, Xiangyu Wang, Kai Fan, Tamara Broderick, David B. Dunson

* 17 pages, 7 figures 

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Locally Adaptive Dynamic Networks


Aug 18, 2016
Daniele Durante, David B. Dunson

* Annals of Applied Statistics (2016). 10, 2203-2232 

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Exploiting Big Data in Logistics Risk Assessment via Bayesian Nonparametrics


Jul 21, 2016
Yan Shang, David B. Dunson, Jing-Sheng Song

* 35 pages, 15 figures 

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Robust and Scalable Bayes via a Median of Subset Posterior Measures


Jun 02, 2016
Stanislav Minsker, Sanvesh Srivastava, Lizhen Lin, David B. Dunson


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Variational Gaussian Copula Inference


May 18, 2016
Shaobo Han, Xuejun Liao, David B. Dunson, Lawrence Carin

* Appearing in Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS) 2016, Cadiz, Spain. JMLR: W&CP volume 51 

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Fast moment estimation for generalized latent Dirichlet models


Mar 23, 2016
Shiwen Zhao, Barbara E. Engelhardt, Sayan Mukherjee, David B. Dunson

* corrected a typo in figure 

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Parallelizing MCMC with Random Partition Trees


Oct 26, 2015
Xiangyu Wang, Fangjian Guo, Katherine A. Heller, David B. Dunson

* 25 pages, 9 figures 

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Bayesian Conditional Density Filtering


Sep 22, 2015
Shaan Qamar, Rajarshi Guhaniyogi, David B. Dunson

* 41 pages, 7 figures, 12 tables 

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Probabilistic Curve Learning: Coulomb Repulsion and the Electrostatic Gaussian Process


Jun 11, 2015
Ye Wang, David B. Dunson

* 16 pages, 6 figures 

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On the consistency theory of high dimensional variable screening


Jun 06, 2015
Xiangyu Wang, Chenlei Leng, David B. Dunson

* adding comments on REC 

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Compressed Gaussian Process


Jun 07, 2014
Rajarshi Guhaniyogi, David B. Dunson

* 33 pages, 8 figures 

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Parallelizing MCMC via Weierstrass Sampler


May 25, 2014
Xiangyu Wang, David B. Dunson

* The original Algorithm 1 removed. Provided some theoretical justification for refinement sampling (Theorem 2). Added a new algorithm in addition to the rejection sampling for handling dimensionality curse. New simulations and graphs (with new colors and designs). A real data analysis is also provided 

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Minimax Optimal Bayesian Aggregation


Mar 06, 2014
Yun Yang, David B. Dunson

* 37 pages 

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Multiscale Dictionary Learning for Estimating Conditional Distributions


Dec 04, 2013
Francesca Petralia, Joshua Vogelstein, David B. Dunson

* Proceeding of Neural Information Processing Systems, Lake Tahoe, Nevada December 2013 

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Nonparametric Bayes dynamic modeling of relational data


Nov 19, 2013
Daniele Durante, David B. Dunson

* Biometrika (2014). 101, 883-898 

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Locally adaptive factor processes for multivariate time series


Jun 21, 2013
Daniele Durante, Bruno Scarpa, David B. Dunson

* Journal of Machine Learning Research (2014), 15: 1493-1522. http://jmlr.org/papers/v15/durante14a.html 

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Learning Densities Conditional on Many Interacting Features


Apr 29, 2013
David C. Kessler, Jack Taylor, David B. Dunson


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Bayesian Compressed Regression


Mar 22, 2013
Rajarshi Guhaniyogi, David B. Dunson

* 29 pages, 4 figures 

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