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On Posterior Concentration in Misspecified Models
v1v2v3v4 (latest)

On Posterior Concentration in Misspecified Models

17 December 2013
R. Ramamoorthi
Karthik Sriram
Ryan Martin
ArXiv (abs)PDFHTML

Papers citing "On Posterior Concentration in Misspecified Models"

8 / 8 papers shown
Title
A comparison of learning rate selection methods in generalized Bayesian
  inference
A comparison of learning rate selection methods in generalized Bayesian inference
Pei-Shien Wu
Ryan Martin
BDL
76
48
0
21 Dec 2020
Gibbs posterior concentration rates under sub-exponential type losses
Gibbs posterior concentration rates under sub-exponential type losses
Nicholas Syring
Ryan Martin
124
29
0
08 Dec 2020
PAC$^m$-Bayes: Narrowing the Empirical Risk Gap in the Misspecified
  Bayesian Regime
PACm^mm-Bayes: Narrowing the Empirical Risk Gap in the Misspecified Bayesian Regime
Warren Morningstar
Alexander A. Alemi
Joshua V. Dillon
130
16
0
19 Oct 2020
Finite mixture models do not reliably learn the number of components
Finite mixture models do not reliably learn the number of components
Diana Cai
Trevor Campbell
Tamara Broderick
66
23
0
08 Jul 2020
Practical calibration of the temperature parameter in Gibbs posteriors
Practical calibration of the temperature parameter in Gibbs posteriors
Lucie Perrotta
50
3
0
22 Apr 2020
Bayesian fractional posteriors
Bayesian fractional posteriors
A. Bhattacharya
D. Pati
Yun Yang
121
110
0
03 Nov 2016
Fast rates in statistical and online learning
Fast rates in statistical and online learning
T. Erven
Peter Grünwald
Nishant A. Mehta
Mark D. Reid
Robert C. Williamson
218
109
0
09 Jul 2015
Inconsistency of Bayesian Inference for Misspecified Linear Models, and
  a Proposal for Repairing It
Inconsistency of Bayesian Inference for Misspecified Linear Models, and a Proposal for Repairing It
Peter Grünwald
T. V. Ommen
147
268
0
11 Dec 2014
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