Peter Grünwald 个人学术档案

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	总计	2019 年至今
引用	8434	3558
h 指数	38	29
i10 指数	78	50

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Tim van ErvenAssociate professor at the University of Amsterdam, the Netherlands在 uva.nl 的电子邮件经过验证
Wouter M. KoolenCentrum Wiskunde & Informatica; University of Twente在 cwi.nl 的电子邮件经过验证
Petri MyllymakiProfessor of Computer Science, University of Helsinki在 helsinki.fi 的电子邮件经过验证
Teemu RoosProfessor at University of Helsinki在 helsinki.fi 的电子邮件经过验证
Rianne de HeideAssistant professor, Mathematics department, Vrije Universiteit Amsterdam在 vu.nl 的电子邮件经过验证
Thijs van OmmenAssistant Professor at Utrecht University在 uu.nl 的电子邮件经过验证
Nishant A. MehtaAssistant Professor, University of Victoria在 uvic.ca 的电子邮件经过验证
Mark PittProfessor, Ohio State University在 osu.edu 的电子邮件经过验证
Joseph HalpernProfessor of Computer Science, Cornell University在 cs.cornell.edu 的电子邮件经过验证
Paul VitanyiCWI and University of Amsterdam在 cwi.nl 的电子邮件经过验证
Philip DawidEmeritus Professor of Statistics, University of Cambridge在 statslab.cam.ac.uk 的电子邮件经过验证
Judith ter SchureAmsterdam UMC在 amsterdamumc.nl 的电子邮件经过验证
Wojciech KotłowskiPoznan University of Technology在 cs.put.poznan.pl 的电子邮件经过验证
Alexander LyCentrum Wiskunde & Informatica在 cwi.nl 的电子邮件经过验证
Richard D. GillEmeritus professor of Mathematical Statistics, Leiden University在 math.leidenuniv.nl 的电子邮件经过验证
Jay MyungProfessor, Department of Psychology, Ohio State University在 osu.edu 的电子邮件经过验证
Peter HarremoesLektor i matematik, Niels Brock在 niels.brock.dk 的电子邮件经过验证
Eric-Jan WagenmakersUniversity of Amsterdam在 uva.nl 的电子邮件经过验证
Glenn ShaferProfessor, Rutgers University在 business.rutgers.edu 的电子邮件经过验证
Robert C. WilliamsonUniversity of Tübingen在 uni-tuebingen.de 的电子邮件经过验证

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Peter Grünwald

Group Leader Machine Learning, CWI; Professor of Statistics, Leiden University

在 cwi.nl 的电子邮件经过验证 - 首页

machine learning statistics information theory foundations of statistics e-values


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
The minimum description length principle PD Grünwald The MIT Press, 2007	2010	2007
A tutorial introduction to the minimum description length principle P Grunwald Advances in Minimum Description Length - Theory and Methods, 2005	641*	2005
Game theory, maximum entropy, minimum discrepancy and robust Bayesian decision theory PD Grünwald, AP Dawid	588	2004
Advances in Minimum Description Length: Theory and Applications PD Grünwald, J Myung, MA Pitt Advances in Minimum Description Length: Theory and Applications, 2005	506	2005
Inconsistency of Bayesian inference for misspecified linear models, and a proposal for repairing it P Grünwald, T Van Ommen	297	2017
Shannon information and Kolmogorov complexity P Grunwald, P Vitányi arXiv preprint cs/0410002, 2004	225	2004
Model selection based on minimum description length P Grünwald Journal of mathematical psychology 44 (1), 133-152, 2000	224	2000
Follow the leader if you can, hedge if you must S de Rooij, T Van Erven, PD Grünwald, WM Koolen Journal of Machine Learning Research (JMLR) 15, 1281-1315, 2014	211	2014
Safe testing P Grünwald, R de Heide, WM Koolen arXiv preprint arxiv:1906.07801, 2020	175	2020
The safe Bayesian P Grünwald International Conference on Algorithmic Learning Theory, 169-183, 2012	165	2012
On discriminative Bayesian network classifiers and logistic regression T Roos, H Wettig, P Grünwald, P Myllymäki, H Tirri Machine Learning 59, 267-296, 2005	165	2005
The minimum description length principle and reasoning under uncertainty PD Grünwald Ph.D. thesis, University of Amsterdam, 1998	161	1998
A minimum description length approach to grammar inference P Grünwald International joint conference on artificial intelligence, 203-216, 1995	151	1995
Kolmogorov complexity and information theory. With an interpretation in terms of questions and answers PD Grünwald, PMB Vitányi Journal of Logic, Language and Information 12 (4), 497-529, 2003	143	2003
Accumulative prediction error and the selection of time series models EJ Wagenmakers, P Grünwald, M Steyvers Journal of Mathematical Psychology 50 (2), 149-166, 2006	129	2006
Fast rates in statistical and online learning T Van Erven, P Grunwald, NA Mehta, M Reid, R Williamson Journal of Machine Learning Research 16, 1793-1861, 2015	111	2015
Fast rates for general unbounded loss functions: from ERM to generalized Bayes PD Grünwald, NA Mehta Journal of Machine Learning Research 21 (56), 1-80, 2020	103*	2020
Suboptimal behavior of Bayes and MDL in classification under misspecification P Grünwald, J Langford Machine Learning 66, 119-149, 2007	98*	2007
The statistical strength of nonlocality proofs W Van Dam, RD Gill, PD Grunwald IEEE transactions on information theory 51 (8), 2812-2835, 2005	97	2005
Catching up faster by switching sooner: a predictive approach to adaptive estimation with an application to the AIC–BIC dilemma T Erven, P Grünwald, S De Rooij Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2012	96	2012

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