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Robust and Scalable Bayes via a Median of Subset Posterior Measures

11 March 2014

Papers citing "Robust and Scalable Bayes via a Median of Subset Posterior Measures"

42 / 42 papers shown

Title
Robust Estimation in metric spaces: Achieving Exponential Concentration with a Fréchet Median Jakwang Kim Jiyoung Park Anirban Bhattacharya 57 1 0 19 Apr 2025
Robust and Scalable Variational Bayes Carlos Misael Madrid Padilla Shitao Fan Lizhen Lin 118 0 0 16 Apr 2025
Learning with Sparsely Permuted Data: A Robust Bayesian Approach Abhisek Chakraborty Saptati Datta 68 0 0 16 Sep 2024
Machine Learning and the Future of Bayesian Computation Steven Winter Trevor Campbell Lizhen Lin Sanvesh Srivastava David B. Dunson TPM 79 4 0 21 Apr 2023
Robust probabilistic inference via a constrained transport metric Abhisek Chakraborty A. Bhattacharya D. Pati 86 3 0 17 Mar 2023
Pigeonhole Stochastic Gradient Langevin Dynamics for Large Crossed Mixed Effects Models Xinyu Zhang Cheng Li 69 0 0 18 Dec 2022
Asynchronous and Distributed Data Augmentation for Massive Data Settings Jiayuan Zhou Kshitij Khare Sanvesh Srivastava 68 3 0 18 Sep 2021
Divide-and-Conquer Bayesian Inference in Hidden Markov Models Chunlei Wang Sanvesh Srivastava 68 9 0 30 May 2021
Divide-and-conquer methods for big data analysis Xueying Chen Jerry Q. Cheng Min‐ge Xie 50 9 0 22 Feb 2021
A Scalable Partitioned Approach to Model Massive Nonstationary Non-Gaussian Spatial Datasets B. Lee Jaewoo Park 93 11 0 26 Nov 2020
$A Linear Transportation $\mathrm{L}^p$ Distance for Pattern Recognition$ A Linear Transportation $\mathrm{L}^p$ Distance for Pattern Recognition Oliver M. Crook Mihai Cucuringu Tim Hurst Carola-Bibiane Schönlieb Matthew Thorpe K. Zygalakis 54 7 0 23 Sep 2020
Robust Optimization and Inference on Manifolds Lizhen Lin Drew Lazar Bayan Sarpabayeva David B. Dunson 38 7 0 11 Jun 2020
A Survey of Bayesian Statistical Approaches for Big Data Farzana Jahan Insha Ullah Kerrie Mengersen 102 14 0 08 Jun 2020
Distributed Bayesian Varying Coefficient Modeling Using a Gaussian Process Prior Rajarshi Guhaniyogi Cheng Li T. Savitsky Sanvesh Srivastava 49 21 0 01 Jun 2020
Informed Proposal Monte Carlo Sarouyeh Khoshkholgh A. Zunino K. Mosegaard 15 14 0 29 May 2020
Quantifying Observed Prior Impact David E. Jones R. Trangucci Yang Chen 13 4 0 29 Jan 2020
An Algorithm for Distributed Bayesian Inference in Generalized Linear Models N. Shyamalkumar Sanvesh Srivastava 38 0 0 18 Nov 2019
Efficiency Assessment of Approximated Spatial Predictions for Large Datasets Yiping Hong Sameh Abdulah M. Genton Ying Sun 85 10 0 11 Nov 2019
Bayesian Robustness: A Nonasymptotic Viewpoint Kush S. Bhatia Yian Ma Anca Dragan Peter L. Bartlett Michael I. Jordan 49 7 0 27 Jul 2019
Optuna: A Next-generation Hyperparameter Optimization Framework Takuya Akiba Shotaro Sano Toshihiko Yanase Takeru Ohta Masanori Koyama 681 5,959 0 25 Jul 2019
Stochastic gradient Markov chain Monte Carlo Christopher Nemeth Paul Fearnhead BDL 83 139 0 16 Jul 2019
Semi-dual Regularized Optimal Transport Marco Cuturi Gabriel Peyré OT 158 51 0 13 Nov 2018
Communication Efficient Parallel Algorithms for Optimization on Manifolds B. Saparbayeva M. Zhang Lizhen Lin 55 4 0 26 Oct 2018
Practical bounds on the error of Bayesian posterior approximations: A nonasymptotic approach Jonathan H. Huggins Trevor Campbell Mikolaj Kasprzak Tamara Broderick 82 28 0 25 Sep 2018
$Solving Non-smooth Constrained Programs with Lower Complexity than $\mathcal{O}(1/\varepsilon)$: A Primal-Dual Homotopy Smoothing Approach$ Solving Non-smooth Constrained Programs with Lower Complexity than $\mathcal{O}(1/\varepsilon)$ : A Primal-Dual Homotopy Smoothing Approach Xiaohan Wei Hao Yu Qing Ling M. Neely 53 16 0 05 Sep 2018
An asymptotic analysis of distributed nonparametric methods Botond Szabó Harry Van Zanten 77 46 0 08 Nov 2017
Generalized Bouncy Particle Sampler Changye Wu Christian P. Robert 93 25 0 15 Jun 2017
Bayesian Bootstraps for Massive Data Andrés F. Barrientos Víctor Pena 43 7 0 28 May 2017
Distributed Statistical Estimation and Rates of Convergence in Normal Approximation Stanislav Minsker Nate Strawn 86 67 0 09 Apr 2017
Distributed Bayesian Matrix Factorization with Limited Communication Xiangju Qin P. Blomstedt Eemeli Leppaaho P. Parviainen Samuel Kaski 75 5 0 02 Mar 2017
Joining and splitting models with Markov melding Robert J. B. Goudie A. Presanis David J. Lunn Daniela De Angelis L. Wernisch 59 30 0 22 Jul 2016
The Zig-Zag Process and Super-Efficient Sampling for Bayesian Analysis of Big Data J. Bierkens Paul Fearnhead Gareth O. Roberts 96 233 0 11 Jul 2016
Robust Probabilistic Modeling with Bayesian Data Reweighting Yixin Wang A. Kucukelbir David M. Blei OOD NoLa 60 12 0 13 Jun 2016
Bayesian inference in hierarchical models by combining independent posteriors Ritabrata Dutta P. Blomstedt Samuel Kaski TPM 43 2 0 30 Mar 2016
Model-free inference on extreme dependence via waiting times J. Johndrow R. Wolpert 19 0 0 24 Dec 2015
Sequential Markov Chain Monte Carlo for Bayesian Filtering with Massive Data A. Freitas Françcois Septier Lyudmila Mihaylova 24 4 0 08 Dec 2015
Nonparametric Bayesian Aggregation for Massive Data Zuofeng Shang Botao Hao Guang Cheng 35 8 0 17 Aug 2015
Optimal approximating Markov chains for Bayesian inference J. Johndrow Jonathan C. Mattingly Sayan Mukherjee David B. Dunson 98 31 0 13 Aug 2015
Accelerated dimension-independent adaptive Metropolis Yuxin Chen David E. Keyes K. Law Hatem Ltaief 52 22 0 18 Jun 2015
Bayesian computation: a perspective on the current state, and sampling backwards and forwards P. Green K. Latuszyñski Marcelo Pereyra Christian P. Robert 129 21 0 04 Feb 2015
Expectation propagation as a way of life: A framework for Bayesian inference on partitioned data Aki Vehtari Andrew Gelman Tuomas Sivula Pasi Jylänki Dustin Tran Swupnil Sahai Paul Blomstedt John P. Cunningham D. Schiminovich Christian P. Robert 110 25 0 16 Dec 2014
Consistency and fluctuations for stochastic gradient Langevin dynamics Yee Whye Teh Alexandre Hoang Thiery Sebastian J. Vollmer 124 235 0 01 Sep 2014