Peter Grünwald

发表

Game theory, maximum generalized entropy, minimum discrepancy, robust Bayes and Pythagoras

A. Philip Dawid, Peter Grünwald, 2002, Proceedings of the IEEE Information Theory Workshop.

Wouter M. Koolen, Thijs van Ommen, Peter Grünwald, 2015, Int. J. Approx. Reason..

Information Theoretic Methods for Bioinformatics

Jukka Heikkonen, Juho Rousu, Jorma Rissanen, 2007, EURASIP J. Bioinform. Syst. Biol..

Optional Stopping with Bayes Factors: a categorization and extension of folklore results, with an application to invariant situations pdf

Peter Grünwald, Allard Hendriksen, Rianne de Heide, 2018, ArXiv.

Prequential plug-in codes that achieve optimal redundancy rates even if the model is wrong

Wojciech Kotlowski, Peter Grünwald, P. Grünwald, 2010, 2010 IEEE International Symposium on Information Theory.

When Ignorance is Bliss

Joseph Y. Halpern, Peter Grünwald, P. Grünwald, 2004, UAI.

Good Listeners, Wise Crowds, and Parasitic Experts

Jan-Willem Romeijn, Peter Grünwald, Tom Sterkenburg, 2012 .

Conference on Learning Theory 2015: Preface

Peter Grünwald, Elad Hazan, Elad Hazan, 2015, COLT.

PAC-Bayes Un-Expected Bernstein Inequality

Peter Grünwald, Benjamin Guedj, Zakaria Mhammedi, 2019, NeurIPS.

RealKrimp - Finding Hyperintervals that Compress with MDL for Real-Valued Data

Wouter Duivesteijn, Arno J. Knobbe, Peter Grünwald, 2014, IDA.

Safe Learning: bridging the gap between Bayes, MDL and statistical learning theory via empirical convexity

Peter Grünwald, John Smith Jones, Jane de Winter, 2011, COLT.

Festschrift in honor of Jorma Rissanen on the occasion of his 75th birthday

Ioan Tabus, Petri Myllymäki, Peter Grünwald, 2008 .

Asymptotic Log-Loss of Prequential Maximum Likelihood Codes

Steven de Rooij, Peter Grünwald, P. Grünwald, 2005, COLT.

Worst-case Optimal Probability Updating pdf

Wouter M. Koolen, Thijs van Ommen, Peter Grünwald, 2015, ArXiv.

The Catch-Up Phenomenon in Bayesian Inference

Peter Grünwald, 2008, COLT.

Entropy concentration and the empirical coding game pdf

Peter Grünwald, P. Grünwald, 2008, ArXiv.

Causation and Nonmonotonic Temporal Reasoning

Peter Grünwald, P. Grünwald, 1997, KI.

Single SignOn Framework

Roland Klemke, Peter Grünwald, 2009 .

The Safe Bayesian - Learning the Learning Rate via the Mixability Gap

Peter Grünwald, P. Grünwald, 2012, ALT.

Christopher S. Wallace Statistical and Inductive Inference by Minimum Message Length. Springer (2005), ISBN 038723795X 432 pp, Hardbound

Peter Grünwald, 2007, Comput. J..

Advances in Minimum Description Length: Theory and Applications

Mark A. Pitt, Peter Grünwald, I. J. Myung, 2005 .

Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning

Wouter M. Koolen, Peter Grünwald, Tim van Erven, 2016, NIPS.

A Tight Excess Risk Bound via a Unified PAC-Bayesian-Rademacher-Shtarkov-MDL Complexity pdf

Peter Grünwald, Nishant A. Mehta, P. Grünwald, 2017, ALT.

A Game-Theoretic Analysis of Updating Sets of Probabilities

Joseph Y. Halpern, Peter Grünwald, P. Grünwald, 2007, UAI.

Mixability in Statistical Learning

Mark D. Reid, Peter Grünwald, Robert C. Williamson, 2012, NIPS.

Adaptive Hedge

Wouter M. Koolen, Steven de Rooij, Peter Grünwald, 2011, NIPS.

Regret and Jeffreys Integrals in Exp. Families pdf

Peter Grünwald, Peter Harremoës, P. Harremoës, 2009, ArXiv.

Probabilistic and Statistical Preliminaries

Peter Grünwald, P. Grünwald, 2007 .

An Empirical Study of MDL Model Selection with Infinite Parametric Complexity pdf

Steven de Rooij, Peter Grünwald, P. Grünwald, 2005, ArXiv.

The Catch-Up Phenomenon

Steven de Rooij, Peter Grünwald, Tim van Erven, 2008, ITW.

Minimum Encoding Approaches for Predictive Modeling pdf

Henry Tirri, Tomi Silander, Petri Myllymäki, 1998, UAI.

Information-Theoretic Preliminaries

Peter Grünwald, P. Grünwald, 2007 .

The 12th Belgian-Dutch Conference on Machine Learning

Henry Tirri, Teemu Roos, Hannes Wettig, 2002 .

When Discriminative Learning of Bayesian Network Parameters Is Easy

Henry Tirri, Teemu Roos, Hannes Wettig, 2003, IJCAI.

Suboptimal Behavior of Bayes and MDL in Classification Under Misspecification

John Langford, Peter Grünwald, J. Langford, 2004, COLT.

Algorithmic information theory pdf

Paul M. B. Vitányi, Peter Grünwald, 2008, ArXiv.

Bounds on Individual Risk for Log-loss Predictors

Wojciech Kotlowski, Peter Grünwald, P. Grünwald, 2011, COLT.

Sequential normalized maximum likelihood in log-loss prediction

Wojciech Kotlowski, Peter Grünwald, P. Grünwald, 2012, 2012 IEEE Information Theory Workshop.

Making Decisions Using Sets of Probabilities: Updating, Time Consistency, and Calibration

Joseph Y. Halpern, Peter Grünwald, P. Grünwald, 2011, J. Artif. Intell. Res..

On predictive distributions and Bayesian networks

Henry Tirri, Tomi Silander, Petri Myllymäki, 2000, Stat. Comput..

Safe Probability: Restricted Conditioning and Extended Marginalization

Peter Grünwald, 2013, ECSQARU.

Uncertainty in artificial intelligence : proceedings of the Twenty-sixth Conference (2010) : July 8-11, 2010, Avalon, CA

Peter Grünwald, Peter Spirtes, Jeff Bilmes, 2010 .

Bayesian and Information-Theories Priors for Bayesian Network Parameters

Henry Tirri, Tomi Silander, Petri Myllymäki, 1998, ECML.

Generalization to Unseen Cases

Henry Tirri, Teemu Roos, Petri Myllymäki, 2005, BNAIC.

On Supervised Learning of Bayesian Network Parameters

Henry Tirri, Teemu Roos, Hannes Wettig, 2002 .

Parametric Models: Prequential Plug-in

Peter Grünwald, P. Grünwald, 2007 .

MDL model selection using the ML plug-in code

Steven de Rooij, Peter Grünwald, P. Grünwald, 2005, ISIT.

Invited review of the book Statistical and Inductive Inference by Minimum Message Length

Peter Grünwald, P. Grünwald, 2006 .

Fast rates in statistical and online learning pdf

Mark D. Reid, Peter Grünwald, Robert C. Williamson, 2015, J. Mach. Learn. Res..

Follow the leader if you can, hedge if you must pdf

Wouter M. Koolen, Steven de Rooij, Peter Grünwald, 2013, J. Mach. Learn. Res..

Switching between Predictors with an Application in Density Estimation

Peter Grünwald, de Steven Rooij, van Tim Erven, 2007 .

A minimum description length approach to grammar inference

Peter Grünwald, P. Grünwald, 1995, Learning for Natural Language Processing.

Fast Rates with Unbounded Losses pdf

Peter Grünwald, Nishant A. Mehta, P. Grünwald, 2016, ArXiv.

The statistical strength of nonlocality proofs

Peter Grünwald, Richard D. Gill, Wim van Dam, 2003, IEEE Transactions on Information Theory.

Kolmogorov Complexity and Information Theory. With an Interpretation in Terms of Questions and Answers

Paul M. B. Vitányi, Peter Grünwald, P. Vitányi, 2003, J. Log. Lang. Inf..

Catching Up Faster by Switching Sooner: A Prequential Solution to the AIC-BIC Dilemma pdf

Steven de Rooij, Peter Grünwald, Tim van Erven, 2008, ArXiv.

On Discriminative Bayesian Network Classifiers and Logistic Regression

Henry Tirri, Teemu Roos, Hannes Wettig, 2005, Machine Learning.

MDL Model Selection

Peter Grünwald, P. Grünwald, 2007 .

Accumulative prediction error and the selection of time series models

Peter Grünwald, Eric-Jan Wagenmakers, Mark Steyvers, 2006 .

Learning the Learning Rate for Prediction with Expert Advice

Wouter M. Koolen, Peter Grünwald, Tim van Erven, 2014, NIPS.

Safe Testing

Wouter M. Koolen, Peter Grünwald, Rianne de Heide, 2019, 2020 Information Theory and Applications Workshop (ITA).

Objectively combining AR5 instrumental period and paleoclimate climate sensitivity evidence

Peter Grünwald, Nicholas Lewis, P. Grünwald, 2018, Climate Dynamics.

Catching Up Faster in Bayesian Model Selection and Model Averaging

Steven de Rooij, Peter Grünwald, Tim van Erven, 2007, NIPS.

Commentary on "The Optimality of Jeffreys Prior for Online Density Estimation and the Asymptotic Normality of Maximum Likelihood Estimators"

Peter Grünwald, 2012, COLT.

Parametric Models: Two-Part

Peter Grünwald, 2007 .

A tutorial introduction to the minimum description length principle

Peter Grünwald, P. Grünwald, 2004, ArXiv.

Safe Probability pdf

Peter Grünwald, P. Grünwald, 2016, ArXiv.

Catching Up Faster by Switching Sooner

Steven de Rooij, Peter Grünwald, Tim van Erven, 2011 .

Bayesian Inconsistency under Misspecification

Peter Grünwald, P. Grünwald, 2006 .

Maximum Entropy and the Glasses You are Looking Through

Peter Grünwald, P. Grünwald, 2000, UAI.

Parametric Models: Bayes

Peter Grünwald, P. Grünwald, 2007 .

Viewing all models as “probabilistic”

Peter Grünwald, 1999, COLT '99.

Strong Entropy Concentration, Game Theory, and Algorithmic Randomness

Peter Grünwald, P. Grünwald, 2001, COLT/EuroCOLT.

Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence (2010) pdf

Peter Grünwald, Peter Spirtes, 2012, ArXiv.

MDL in Context

Peter Grünwald, P. Grünwald, 2007 .

Maximum Likelihood vs. Sequential Normalized Maximum Likelihood in On-line Density Estimation

Wojciech Kotlowski, Peter Grünwald, P. Grünwald, 2011, COLT.

Learning, Regularity, and Compression

Peter Grünwald, 2007 .

Finiteness of redundancy, regret, Shtarkov sums, and Jeffreys integrals in exponential families

Peter Grünwald, Peter Harremoës, P. Harremoës, 2009, ISIT.

Shannon Information and Kolmogorov Complexity

Paul M. B. Vitányi, Peter Grünwald, P. Vitányi, 2004, ArXiv.

Suboptimal behavior of Bayes and MDL in classification under misspecification

John Langford, Peter Grünwald, J. Langford, 2004, Machine Learning.

Horizon-Independent Optimal Prediction with Log-Loss in Exponential Families

Peter L. Bartlett, Wojciech Kotlowski, Fares Hedayati, 2013, COLT.

Log-optimal anytime-valid E-values

Wouter M. Koolen, Peter Grünwald, P. Grünwald, 2021, International Journal of Approximate Reasoning.

PAC-Bayes, MAC-Bayes and Conditional Mutual Information: Fast rate bounds that handle general VC classes pdf

Thomas Steinke, Peter Grünwald, Lydia Zakynthinou, 2021, COLT.

Minimax risk classifiers with 0-1 loss pdf

Santiago Mazuelas, Peter Grünwald, Mauricio Romero, 2022, ArXiv.

Safe Tests and Always-Valid Confidence Intervals for contingency tables and beyond pdf

Peter Grünwald, Alexander Ly, Rosanne Turner, 2021, ArXiv.

The Minimum Description Length Principle and Non - Deductive Inference

Peter Grünwald, P. Grünwald, 1997 .

Jeffreys versus Shtarkov distributions associated with some natural exponential families

Peter Grünwald, Peter Harremoës, Shaul K. Bar-Lev, 2010 .

Using Stacking to Average Bayesian Predictive Distributions (with Discussion)

Peter Grünwald, R. de Heide, 2018 .

A First Look at the Minimum Description Length Principle

Peter Grünwald, P. Grünwald, 2006 .

Luckiness and Regret in Minimum Description Length Inference

Steven de Rooij, Peter Grünwald, P. Grünwald, 2011 .

The statistical strength of nonlocality proofs : the strength of a nonlocality

Peter Grünwald, Richard D. Gill, R. Gill, 2003 .