For articles in Dutch, click here.
Book
Preprints
Refereed and Invited Publications
This includes also my books, coedited books and invited papers, commentaries
and reviews of other papers/books (marked by (I)). Other nonrefereed
publications (contributions to popular magazines, invited conference abstracts,
papers, Ph.D. thesis, workshop papers) can be found further below.
2017
2016
 Peter
D. Grünwald.
Contextuality of Misspecification and
DataDependent Losses: Comment on Watson and Holmes (2016)
In Statistical Science 31(4), pages 495 498, December 2016.
 Wouter Koolen, Peter
D. Grünwald and T. van Erven.
Combining adversarial guarantees and stochastic fast rates in online
learning
In Advances in Neural Information Processing Systems (NIPS) 29, pages 44574465, December 2016.
 Peter
D. Grünwald. Toetsen als Gokken: een redelijk alternatief voor de pwaarde (in Dutch). Nieuw Archief voor Wiskunde 5/17 Nr 4., December 2016.
 Thijs van Ommen, Wouter M. Koolen, Thijs E. Feenstra and
Peter
D. Grünwald. Robust
Probability Updating. International Journal of Approximate
Reasoning, vol. 74, pp. 3057, July 2016.
 R. Shiffrin, S. Chandramouli, and P.D. Grünwald. Bayes
Factors, Relations to Minimum Description Length, and
Overlapping Model Classes. Journal of
Mathematical Psychology, vol 72, pp. 5677, 2016.
 K. Oikonomou and P.D. Grünwald. Explicit Bounds for Entropy Concentration under Linear Constraints. Available on arXiv as
arXiv:1107.6004. IEEE Transactions on Information Theory, vol. 62, nr. 3, pp. 12061230, 2016.
2015
 T. van Erven, P.D. Grünwald, N. Mehta, M. Reid and
R. Williamson. Fast
Rates in Statistical and Online Learning.
Journal of Machine Learning Research, vol. 16,
pp. 17931861, 2015, Special issue
dedicated to the Memory of Alexey Chervonenkis, 2015.
2014
2013
 P.D. Grünwald. Safe Probability: restricted
conditioning and extended marginalization. Proceedings
Twelfth European Conference on Symbolic and Quantitative
Approaches to Reasoning with Uncertainty (ECSQARU
2013). Lecture Notes in Computer Science, Vol. 7958, Springer
Verlag 2013, pages 242253.
 P. Bartlett, P. Grünwald, P. Harremoes, F.
Hedayati, W. Kotlowski.
HorizonIndependent Optimal Prediction with LogLoss in Exponential
Families, JMLR Workshop and Conference Proceedings 30, COLT 2013: 662695, 2013.
2012
 J.W. Romeijn, T. Sterkenburg and
P.D. Grünwald. Good
Listeners, Wise Crowds and Parasitic Experts
(I). Comment on MetaInduction and the Wisdom of
Crowds by Paul D. Thorn and Gerhard Schurz. Analyse
& Kritik 34(2), pages 399408, 2012.
 T. van Erven, P.D. Grünwald, M.D. Reid and R.C. Williamson Mixability in Statistical Learning. Advances in Neural Information
Processing Systems 24 (NIPS 2012) (longer version with proofs included).
 P.D. Grünwald. The
Safe Bayesian: learning the learning rate via the
mixability gap. Proceedings 23rd International
Conference on Algorithmic Learning Theory (ALT '12),
Copyright © 2012 Springer Verlag. The link
is to a slightly longer version than the conference paper,
including the proof of Theorem 3 and a little additional
discussion.
 P.D. Grünwald. Commentary on The Optimality of Jeffreys Prior for Online Density Estimation and the Asymptotic Normality of Maximum Likelihood Estimators by F. Hedayati and P. Bartlett (I).
JMLR Workshop and Conference Proceedings
Volume 23, COLT 2012: 7.14  7.17, 2012
 T. van Erven and
P.D. Grünwald and S. de
Rooij. Catching Up Faster by Switching Sooner: A Predictive
Approach to Adaptive Estimation with an application to the
AICBIC Dilemma. Journal of
the Royal Statistical Society, Series B 74(3), 361397
(with discussion, pp. 397417), 2012. Presented as a
``Read Paper'' at
the RSS Ordinary Meeting 19 October 2011. Preprint.
Matlab code
.
2011
 P.D. Grünwald and J.Y. Halpern. Making
Decisions Using Sets of Probabilities: Updating, Time
Consistency, and Calibration. Journal of Artificial
Intelligence Research (JAIR) 42, pages 393426, 2011.
 T. van Erven, P.D. Grünwald , W. Koolen and S. de Rooij. Adaptive Hedge. Advances in Neural Information
Processing Systems 24 (NIPS 2011), pp. 16561664, Granada, Spain, 2011.
 P.D. Grünwald. Safe
Learning: bridging the gap between Bayes, MDL and statistical
learning theory via empirical convexity. Proceedings
24th Conference on Learning Theory (COLT 2011),
pp. 551573, Budapest, 2011.
 W. Kotlowski and P.D. Grünwald. Maximum Likelihood
vs. Sequential Normalized Maximum Likelihood in Online Density
Estimation. Proceedings 24th Conference on Learning
Theory (COLT 2011), pp. 761779. Budapest, 2011.
 S. de Rooij and P.D. Grünwald. Luckiness
and Regret in Minimum Description Length Inference. Handbook of
the Philosophy of Science, Volume 7: Philosophy of Statistics
(edited by Prasanta S. Bandyopadhyay and Malcolm Forster), pages 865900. Elsevier
Science Publishers, 2011, ISBN 0444518622.
2010
 S. K. BarLev, D. Bshouty, P.D. Grünwald and P. Harremoes.
Jeffreys vs. Shtarkov Distributions Associated with Some Natural Exponential
Families. Statistical Methodology (2010),
doi:10.1016/j.stamet.2010.06.001, in press.
 P.D. Grünwald and W. Kotlowski Prequential PlugIn Codes that Achieve Optimal Redundancy Rates even if the Model is Wrong
(the link is to an extended version containing proofs of the main
results). Proceedings of the 2010 International Symposium on
Information Theory (ISIT 2010), Houston, Texas, 2010.
 W. Kotlowski, P.D. Grünwald and S. de Rooij.
Following the Flattened Leader. Proceedings 23rd Conference on Learning Theory (COLT 2010), Haifa, 2010.
2009
2008
 P.D. Grünwald. That Simple Device Already Used By
Gauss. In Festschrift in Honor of Jorma Rissanen on the
Occasion of his 75th
Birthday, Tampere University Press, 2008.
 R.D. Gill and
P.D. Grünwald. An Algorithmic and a
Geometric Characterization of Coarsening at
Random. Annals of
Statistics 36(5), pages 24092422, 2008.
 P.D. Grünwald and J.Y. Halpern. A GameTheoretic Analysis
of Updating Sets of Probabilities . Proceedings of the
TwentyFourth Annual
Conference on Uncertainty in Artificial Intelligence (UAI
2008), pages 240247,
Helsinki, Finland, July 2008. The link is to a
longer version of the paper (math/CS
arXiv, arXiv:0711.3235v1, 2007), including the proofs that are
left out of the conference version. Paper now superseded by
our 2011 JAIR paper.
 P.D. Grünwald and
P.M.B. Vitányi.
Algorithmic Information Theory.
In Handbook of the Philosophy of Science, Volume 8: Philosophy of
Information. (edited
by P. Adriaans and J. van Benthem), pp 289325. Elsevier
Science Publishers, 2008.
 P.D. Grünwald. Entropy Concentration and the Empirical
Coding Game. Statistica Neerlandica 62(3), pages
374392, 2008. Special Issue: Eurandom 19982008: A random
tour through a decade of research. Here is a slightly
modified version.
 P.D. Grünwald, P. Myllymäki,
I. Tabus, M. Weinberger and B. Yu (editors). Festschrift in Honor of Jorma Rissanen on the
Occasion of his 75th
Birthday. Tampere University Press, 2008.
2007
2006

P.D. Grünwald. Bayesian Inconsistency under Misspecification.
Four page abstract of a plenary presentation at the
Valencia 8 ISBA conference on Bayesian
statistics, June 2006 (the link is to a slightly extended
version of the abstract).

P.D. Grünwald. Review of the book
Statistical and Inductive Inference by Minimum Message Length
by Chris Wallace, Springer 2005. \(I)
Computer
Journal, June 2006.
 S. de Rooij and
P.D. Grünwald. An Empirical Study of MDL Model Selection with
Infinite Parametric Complexity. Journal of
Mathematical Psychology 50(2), pages 180192, 2006.
 E.J. Wagenmakers,
P.D. Grünwald and M. Steyvers. Accumulative prediction error and the selection of time
series models. Journal of
Mathematical Psychology 50(2), pages 149166, 2006.
 E.J.
Wagenmakers and
P.D. Grünwald. A
Bayesian perspective on hypothesis testing: a Comment on Killeen (2005). Psychological
Science 17(7), pages 641642, 2006.
 P. Grünwald. A First Look at the Minimum Description Length
Principle. Chapter 12 in Intelligent Algorithms in Ambient
and Biomedical Computing (edited
by W. Verhaegh, E. Aarts, and J. Korst), pp 187213. Philips Research Book
Series, Vol. 7, SpringerVerlag.
2005
 T. Roos, , P. Grünwald, P. Myllymäki and H.Tirri.
Generalization
to Unseen Cases. Advances in Neural Information
Processing Systems 18 (NIPS 2005), pages 11291136, 2006.
 S. de Rooij and
P.D. Grünwald. MDL Model
Selection using the ML Plugin Code. Proceedings of the 2005 IEEE
International Symposium on Information Theory (ISIT 2005),
September 2005.
 W. van Dam, R.D. Gill and
P.D. Grünwald. The statistical strength
of nonlocality proofs. IEEE
Transactions on Information Theory 51(8), 28122835, August 2005.
 T. Roos, H. Wettig, P. Grünwald, P. Myllymäki and H.Tirri.
On discriminative
Bayesian Network classifiers and logistic regression. Machine
Learning 59(3), pages 267  296, 2005.
 P.D. Grünwald and S. de Rooij. Asymptotic
LogLoss of Prequential Maximum Likelihood Codes. Proceedings of the Eighteenth Annual
Conference on Learning Theory (COLT 2005),
pages 652667, June 2005.

P.D. Grünwald, I.J. Myung, M. Pitt (editors). Advances in
Minimum Description Length: Theory and
Applications. MIT
Press, 2005.
 P. Grünwald. A Tutorial
Introduction to the Minimum Description
Length Principle. Chapters
1 and 2 of Advances in Minimum Description Length:
Theory and Applications (edited by P. Grünwald, I.J. Myung,
M.A. Pitt), MIT Press, April 2005. (80 pages; postscript and PDF).
Errata can be found here.
2004
 P.D. Grünwald and A.P. Dawid. Game theory,
maximum entropy, minimum discrepancy, and robust Bayesian decision
theory. Annals of Statistics 32(4), pages 13671433, 2004.
 P.D. Grünwald and J. Halpern. When
ignorance is bliss. Proceedings of the
Twentieth Annual
Conference on Uncertainty in Artificial Intelligence (UAI 2004),
Banff, Canada,
July 2004.
 P.D. Grünwald and J. Langford. Suboptimal behaviour of Bayes and MDL in classification under misspecification. Proceedings of the Seventeenth Annual
Conference on Learning Theory (COLT 2004),
July 2004 (the paper on this webpage is a slight extension
of the conference paper, containing two extra
pages of discussion).
2003
 P.D. Grünwald and
P.M.B. Vitányi. Kolmogorov complexity and information theory
with an interpretation in terms of questions and answers
. Journal of Logic, Language and Information 12, pages 497529, 2003. Click here for postscript and here for pdf.
 P.D. Grünwald and J. Halpern. Updating
probabilities. Journal of Artificial Intelligence Research
(JAIR) 19, pages 243278, 2003.
 H. Wettig,
P. Grünwald, T. Roos, P. Myllymäki and H.Tirri.
When discriminative learning of Bayesian network
parameters is easy. In Proceedings of the
Eighteenth International Joint Conference on Artificial
Intelligence (IJCAI 2003),
pages 491496, Acapulco, Mexico, August 2003
(postscript or
pdf ).
2002
 P. Grünwald and
J. Halpern. Updating
probabilities.
In Proceedings of the Eighteenth Annual
Conference on Uncertainty in Artificial Intelligence (UAI 2002),
pages 187196, University of Alberta, Edmonton, Canada,
August 2002. ( postscript or pdf)
 P. Grünwald,
P. Kontkanen, P. Myllymäki,
T. Roos and H. Tirri. Supervised posterior
distributions. Abstract, presented at the 7th Valencia
International Meeting on Bayesian Statistics, Tenerife, Spain,
June 2002.
 P. Grünwald. Taking the sting out of
subjective probability In Words, Proofs, and Diagrams (editors D.
BarkerPlummer, D. Beaver, J. van Benthem and P. Scotto Di
Luzio), pages 7594. CSLI
Publications, Stanford, CA, June 2002.
2001
2000
 P.D. Grünwald. Model
selection based on minimum description length, Journal of Mathematical
Psychology 44, pages 133152, 2000. (if you are
interested in learning about MDL, please refer to my much
more recent Minimum Description
Length
Tutorial cited above; the JMP article is somewhat dated).
 P.Kontkanen, P. Myllymäki,
T. Silander, H.Tirri, and P.D. Grünwald. Predictive distributions and
Bayesian networks, Journal of Statistics and Computing 10, pages
3954, 2000.
 P. Grünwald. Maximum entropy and the
glasses you are looking through. In Proceedings of the Sixteenth Annual
Conference on Uncertainty in Artificial Intelligence (UAI 2000),
pages 238246. Stanford, CA, USA,
July 2000.
1999
 P. Grünwald. Viewing all models as
'probabilistic'. In Proceedings of the Twelfth Annual Conference on
Computational Learning Theory (COLT' 99), pages
171182. Santa Cruz, CA, USA, July 1999.
1998
 P. Grünwald,
P.Kontkanen,
P. Myllymäki, T. Silander and H.Tirri. Minimum
encoding approaches for predictive modeling. In
Proceedings of the Fourteenth
International Conference on Uncertainty in Artificial Intelligence
(UAI'98), pages 183192. Madison, WI, USA, July 1998.
 P.Kontkanen, P. Myllymäki,
T. Silander, H.Tirri, and P. Grünwald. Bayesian
and informationtheoretic priors for Bayesian network parameters, pages
8994 in Machine Learning: ECML98, Proceedings of the 10th European
Conference, edited by C.Nédellec and C.Rouveirol, pages 8994. Vol. 1398 in Lecture
Notes in Artificial Intelligence, SpringerVerlag, 1998.
 P.Kontkanen, P.Myllymäki,
T.Silander, H.Tirri, and P. Grünwald. On
the small sample size behavior of Bayesian and informationtheoretic
approaches for predictive inference. Abstract, presented at the 6th Valencia
International Meeting on Bayesian Statistics, Alcossebre, Spain,
MayJune 1998.
 P. Grünwald. Ramifications and
sufficient causes. Abstract, presented at the Fourth Symposium on Logical Formalizations
of Common Sense Reasoning (Common Sense '98), London 1998.
1997
 P.Kontkanen, P. Myllymäki,
T. Silander, H.Tirri, and P. Grünwald. Comparing predictive
inference methods for discrete domains. In Proceedings of the Sixth International Workshop on
Artificial Intelligence and Statistics (AISTATS '97), pages 311318. Fort
Lauderdale, Florida, 1997.
 P. Grünwald. Causation and
nonmonotonic temporal reasoning. In KI97: Advances in Artificial
Intelligence (editors G. Brewka, C. Habel and B. Nebel), pages 159170;
Lecture Notes in Artificial Intelligence no. 1303. Springer Verlag,
Berlin, Germany, 1997.
1996
Nonrefereed Publications and Publications at Local Meetings
Articles for Popular Magazines
(in Dutch)
 P. Grünwald. Kansloos: van Willem Ruis tot Lucia de Berk (in
Dutch). Deel I (Bilogical 1(2), December
2008). Deel II (Bilogical 2(1), Juni 2009).
Invited Paper
Ph.D. Thesis
P. Grünwald. The Minimum Description Length Principle and
Reasoning under Uncertainty, ILLC Dissertation series
199803, University of Amsterdam, 1998. Click here.
Technical Reports
Publications at Workshops and Local
Conferences
 T. van Erven and S. de Rooij and Peter Grünwald. Switching between Predictors with an Application in Density
Estimation. Proceedings of the 28th Symposium on
Information Theory in the Benelux, Enschede, The
Netherlands, 2007.
 T. Roos, , P. Grünwald, P. Myllymäki and H.Tirri.
Generalization to Unseen Cases. In Proceedings BNAIC '05 (BelgiumNetherlands
conference on Artificial Intelligence),
Bruxelles, Belgium, October 2005 Winner of Best Paper Award!

P. Grünwald and J. Halpern. Updating probabilities
(abstract). In Proceedings BNAIC '03 (BelgiumNetherlands
conference on Artificial Intelligence) ,
Nijmegen, the Netherlands,
October 2003.
 H. Wettig,
P. Grünwald, T. Roos, P. Myllymäki and
H. Tirri. Supervised learning of Bayesian network parameters made
easy. In Proceedings BeNeLearn
'02 (BelgiumNetherlands conference on Machine Learning),
Utrecht, the Netherlands,
2002.
 P.Kontkanen, P. Myllymäki,
T. Silander, H.Tirri, and P. Grünwald. On
predictive distributions and Bayesian networks. In Proceedings BeNeLearn
'97 (BelgiumNetherlands conference on Machine Learning),
Tilburg, the Netherlands, 1997.
 P.Kontkanen, P. Myllymäki,
T. Silander, H.Tirri, and P. Grünwald. Comparing
predictive inference methods for discrete domains. Pages 311318 in Proceedings
of the Sixth International Workshop on Artificial Intelligence and
Statistics (Ft. Lauderdale, USA, January 1997).
 P. Grünwald. The minimum
description length principle and nondeductive inference. Proceedings
IJCAI Workshop on Abduction and Induction in AI (editor P. Flach), Nagoya,
Japan 1997.
 P. Grünwald. Nonmonotonic
temporal reasoning as a search for explanations. NRAC '97 (Second
IJCAI Workshop on Nonmonotonic Reasoning, Action and Change), Nagoya,
Japan, 1997.
 P. Grünwald. Causation,
explanation and persistence. In Proceedings 1997 Dutch German Workshop on
Nonmonotonic Reasoning, pages 149158, Saarbrücken 1997.
 P. Grünwald. Causal
networks and nonmonotonic temporal reasoning. In Proceedings 1996 Dutch
Conference on Artificial Intelligence (NAIC96), pages 157166, nominated
for Best Paper Award, Utrecht 1996.
 P. Grünwald, B. Gaume and
M. Bouajjani. A new causal theory of action. In Proceedings 1995 Dutch
Conference on Artificial Intelligence (NAIC95), Rotterdam 1995.
Last updated: January 2012.
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