Peter Grünwald

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Tim van ErvenAssociate professor at the University of Amsterdam, the NetherlandsVerified email at uva.nl
Wouter M. KoolenCentrum Wiskunde & Informatica; University of TwenteVerified email at cwi.nl
Petri MyllymakiProfessor of Computer Science, University of HelsinkiVerified email at helsinki.fi
Teemu RoosProfessor at University of HelsinkiVerified email at helsinki.fi
Nishant A. MehtaAssistant Professor, University of VictoriaVerified email at uvic.ca
Thijs van OmmenAssistant Professor at Utrecht UniversityVerified email at uu.nl
Rianne de HeideAssistant professor, Mathematics department, Vrije Universiteit AmsterdamVerified email at vu.nl
Mark PittProfessor, Ohio State UniversityVerified email at osu.edu
Joseph HalpernProfessor of Computer Science, Cornell UniversityVerified email at cs.cornell.edu
Paul VitanyiCWI and University of AmsterdamVerified email at cwi.nl
Wojciech KotłowskiPoznan University of TechnologyVerified email at cs.put.poznan.pl
Philip DawidEmeritus Professor of Statistics, University of CambridgeVerified email at statslab.cam.ac.uk
Jay MyungProfessor, Department of Psychology, Ohio State UniversityVerified email at osu.edu
Judith ter SchureAmsterdam UMCVerified email at amsterdamumc.nl
Alexander LyCentrum Wiskunde & InformaticaVerified email at cwi.nl
Richard D. GillProfessor of Mathematical Statistics, Leiden UniversityVerified email at math.leidenuniv.nl
Eric-Jan WagenmakersUniversity of AmsterdamVerified email at uva.nl
Robert C. WilliamsonUniversity of TübingenVerified email at uni-tuebingen.de
Mark D. ReidAppleVerified email at reid.name
Wim van DamMicrosoftVerified email at microsoft.com

Peter Grünwald

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

Verified email at cwi.nl - Homepage

machine learning statistics information theory foundations of probability statistics and the law


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
The minimum description length principle PD Grünwald The MIT Press, 2007	1864	2007
A tutorial introduction to the minimum description length principle P Grunwald Advances in Minimum Description Length - Theory and Methods, 2005	591*	2005
Game theory, maximum entropy, minimum discrepancy and robust Bayesian decision theory PD Grünwald, AP Dawid	545	2004
Advances in Minimum Description Length: Theory and Applications PD Grünwald, J Myung, MA Pitt Advances in Minimum Description Length: Theory and Applications, 2005	482	2005
Inconsistency of Bayesian inference for misspecified linear models, and a proposal for repairing it P Grünwald, T Van Ommen	229	2017
Model selection based on minimum description length P Grünwald Journal of mathematical psychology 44 (1), 133-152, 2000	214	2000
Shannon information and Kolmogorov complexity P Grunwald, P Vitányi arXiv preprint cs/0410002, 2004	210	2004
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	190	2014
The minimum description length principle and reasoning under uncertainty PD Grünwald Ph.D. thesis, University of Amsterdam, 1998	159	1998
On discriminative Bayesian network classifiers and logistic regression T Roos, H Wettig, P Grünwald, P Myllymäki, H Tirri Machine learning 59, 267-296, 2005	157	2005
A minimum description length approach to grammar inference P Grünwald Connectionist, Statistical and Symbolic Approaches to Learning for Natural …, 1996	150	1996
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	135	2003
The safe Bayesian P Grünwald International Conference on Algorithmic Learning Theory, 169-183, 2012	124*	2012
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	121	2006
Safe testing P Grünwald, R de Heide, WM Koolen arXiv preprint arxiv:1906.07801, 2020	106	2020
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
The statistical strength of nonlocality proofs W Van Dam, RD Gill, PD Grunwald IEEE transactions on information theory 51 (8), 2812-2835, 2005	92	2005
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	91	2015
Updating probabilities P Grünwald, JY Halpern J. Artif. Intell. Res.(JAIR) 19, 243-278, 2003	89	2003
Fast rates for general unbounded loss functions: from ERM to generalized Bayes PD Grünwald, NA Mehta The Journal of Machine Learning Research 21 (1), 2040-2119, 2020	87*	2020

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