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Related papers: Comment: Bayesian Checking of the Second Levels of…

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We provide comments on the article "High-dimensional simultaneous inference with the bootstrap" by Ruben Dezeure, Peter Buhlmann and Cun-Hui Zhang.

Methodology · Statistics 2017-08-29 Jelena Bradic , Yinchu Zhu

In this work, we offer a thorough analytical investigation into the role of shared hyperparameters in a hierarchical Bayesian model, examining their impact on information borrowing and posterior inference. Our approach is rooted in a…

Methodology · Statistics 2025-09-23 Prasenjit Ghosh , Anirban Bhattacharya , Debdeep Pati

Bayesian network is a complete model for the variables and their relationships, it can be used to answer probabilistic queries about them. A Bayesian network can thus be considered a mechanism for automatically applying Bayes' theorem to…

Artificial Intelligence · Computer Science 2010-11-08 Jianguo Ding

We comment the recent published article entitled "Temperature dependent fluctuations in the two-dimensional XY model", appeared in J. Phys. A: Math.Gen. 38 (2005) 5603.

Statistical Mechanics · Physics 2007-05-23 G. Palma

In this note a criterion for Cauchy sequences is proved which refines the one presented in `Cauchy sequences in b-metric spaces', Topology Appl. 373 (2025) 109477.

General Topology · Mathematics 2026-04-17 Lech Pasicki

We propose Posterior Bootstrap, a set of algorithms extending Weighted Likelihood Bootstrap, to properly incorporate prior information and address the problem of model misspecification in Bayesian inference. We consider two approaches to…

Methodology · Statistics 2021-04-19 Emilia Pompe

Rejoinder of "Bayesian Models and Methods in Public Policy and Government Settings" by S. E. Fienberg [arXiv:1108.2177]

Methodology · Statistics 2011-08-22 Stephen E. Fienberg

A note on "Bayesian nonparametric estimators derived from conditional Gibbs structures" by Antonio Lijoi, Igor Pr\"{u}nster, Stephen G. Walker [arXiv:0808.2863].

Probability · Mathematics 2014-01-17 Antonio Lijoi , Igor Prünster , Stephen G. Walker

This paper investigates Bayesian variable selection when there is a hierarchical dependence structure on the inclusion of predictors in the model. In particular, we study the type of dependence found in polynomial response surfaces of…

Methodology · Statistics 2015-02-03 Daniel Taylor-Rodriguez , Andrew Womack , Nikolay Bliznyuk

Potential violent criminals will often need to go through a sequence of preparatory steps before they can execute their plans. During this escalation process police have the opportunity to evaluate the threat posed by such people through…

Machine Learning · Computer Science 2019-11-06 F. O. Bunnin , J. Q. Smith

Items in modern recommender systems are often organized in hierarchical structures. These hierarchical structures and the data within them provide valuable information for building personalized recommendation systems. In this paper, we…

Machine Learning · Computer Science 2019-08-21 Zitao Liu , Zhexuan Xu , Yan Yan

We comment on Z. D. Zhang's Response [arXiv:0812.2330] to our recent Comment [arXiv:0811.3876] addressing the conjectured solution of the three-dimensional Ising model reported in [arXiv:0705.1045].

Statistical Mechanics · Physics 2009-11-13 F. Y. Wu , B. M. McCoy , M. E. Fisher , L. Chayes

This paper is devoted to the description of complex finite-dimensional algebras of level two. We obtain the classification of algebras of level two in the varieties of Jordan, Lie and associative algebras.

Rings and Algebras · Mathematics 2015-12-09 A. Kh. Khudoyberdiyev

Rejoinder of ``Statistical analysis of an archeological find'' [arXiv:0804.0079]

Applications · Statistics 2008-12-18 Andrey Feuerverger

The problem of selection, storage, search and analysis of information about the state, functioning and interaction of elements of complex hierarchical network systems is considered. The principles of construction of information models of…

Physics and Society · Physics 2021-06-17 Olexandr Polishchuk , Mykhailo Yadzhak

We learn multiple hypotheses for related tasks under a latent hierarchical relationship between tasks. We exploit the intuition that for domain adaptation, we wish to share classifier structure, but for multitask learning, we wish to share…

Machine Learning · Computer Science 2014-08-12 Hal Daume

We learn multiple hypotheses for related tasks under a latent hierarchical relationship between tasks. We exploit the intuition that for domain adaptation, we wish to share classifier structure, but for multitask learning, we wish to share…

Machine Learning · Computer Science 2009-07-07 Hal Daumé

Rejoinder: Expert Elicitation for Reliable System Design [arXiv:0708.0279]

Methodology · Statistics 2009-09-29 Tim Bedford , John Quigley , Lesley Walls

This is a Comment on the Article ``Aging, phase ordering and conformal invariance'' by M.Henkel, M.Pleimling, C.Godr\`eche and J.M.Luck [Phys.Rev.Lett. 87, 265701 (2001)].

Statistical Mechanics · Physics 2009-11-07 Federico Corberi , Eugenio Lippiello , Marco Zannetti

Multilevel models (MLMs) are a central building block of the Bayesian workflow. They enable joint, interpretable modeling of data across hierarchical levels and provide a fully probabilistic quantification of uncertainty. Despite their…