Peter Grünwald

Publication Activity (10 Years)

Years Active: 1995-2023
Publications (10 Years): 21

Top Topics

Conditional Mutual Information

Minimum Description Length

Top Venues

Publications

Peter Harremoës, Tyron Lardy, Peter Grünwald
Universal Reverse Information Projections and Optimal E-statistics. CoRR (2023)
Peter Harremoës, Tyron Lardy, Peter Grünwald
Universal Reverse Information Projections and Optimal E-statistics. ISIT (2023)
Santiago Mazuelas, Mauricio Romero, Peter Grünwald
Minimax risk classifiers with 0-1 loss. CoRR (2022)
Hugo Manuel Proença, Peter Grünwald, Thomas Bäck, Matthijs van Leeuwen
Robust subgroup discovery. Data Min. Knowl. Discov. 36 (5) (2022)
Aaditya Ramdas, Peter Grünwald, Vladimir Vovk, Glenn Shafer
Game-theoretic statistics and safe anytime-valid inference. CoRR (2022)
Wouter M. Koolen, Peter Grünwald
Log-optimal anytime-valid E-values. Int. J. Approx. Reason. 141 (2022)
Peter Grünwald, Alexander Ly, Muriel Perez-Ortiz, Judith Ter Schure
The Safe Logrank Test: Error Control under Optional Stopping, Continuation and Prior Misspecification. SPACA (2021)
Peter Grünwald, Thomas Steinke, Lydia Zakynthinou
PAC-Bayes, MAC-Bayes and Conditional Mutual Information: Fast rate bounds that handle general VC classes. COLT (2021)
Peter Grünwald, Thomas Steinke, Lydia Zakynthinou
PAC-Bayes, MAC-Bayes and Conditional Mutual Information: Fast rate bounds that handle general VC classes. CoRR (2021)
Rosanne Turner, Alexander Ly, Peter Grünwald
Safe Tests and Always-Valid Confidence Intervals for contingency tables and beyond. CoRR (2021)
Hugo Manuel Proença, Peter Grünwald, Thomas Bäck, Matthijs van Leeuwen
Discovering Outstanding Subgroup Lists for Numeric Targets Using MDL. ECML/PKDD (1) (2020)
Peter Grünwald, Rianne de Heide, Wouter M. Koolen
Safe Testing. ITA (2020)
Hugo Manuel Proença, Peter Grünwald, Thomas Bäck, Matthijs van Leeuwen
Discovering outstanding subgroup lists for numeric targets using MDL. CoRR (2020)
Peter Grünwald, Teemu Roos
Minimum Description Length Revisited. CoRR (2019)
Peter Grünwald, Rianne de Heide, Wouter M. Koolen
Safe Testing. CoRR (2019)
Rianne de Heide, Alisa Kirichenko, Nishant A. Mehta, Peter Grünwald
Safe-Bayesian Generalized Linear Regression. CoRR (2019)
Zakaria Mhammedi, Peter Grünwald, Benjamin Guedj
PAC-Bayes Un-Expected Bernstein Inequality. NeurIPS (2019)
Allard Hendriksen, Rianne de Heide, Peter Grünwald
Optional Stopping with Bayes Factors: a categorization and extension of folklore results, with an application to invariant situations. CoRR (2018)
Wouter M. Koolen, Peter Grünwald, Tim van Erven
Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning. CoRR (2016)
Wouter M. Koolen, Peter Grünwald, Tim van Erven
Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning. NIPS (2016)
Peter Grünwald
Safe Probability. CoRR (2016)
Peter Grünwald, Elad Hazan
Conference on Learning Theory 2015: Preface. COLT (2015)
Jouke Witteveen, Wouter Duivesteijn, Arno J. Knobbe, Peter Grünwald
RealKrimp - Finding Hyperintervals that Compress with MDL for Real-Valued Data. IDA (2014)
Wouter M. Koolen, Tim van Erven, Peter Grünwald
Learning the Learning Rate for Prediction with Expert Advice. NIPS (2014)
Peter Grünwald
Safe Probability: Restricted Conditioning and Extended Marginalization. ECSQARU (2013)
Peter Grünwald, Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri
Minimum Encoding Approaches for Predictive Modeling CoRR (2013)
Peter L. Bartlett, Peter Grünwald, Peter Harremoës, Fares Hedayati, Wojciech Kotlowski
Horizon-Independent Optimal Prediction with Log-Loss in Exponential Families. COLT (2013)
Peter Grünwald
The Safe Bayesian - Learning the Learning Rate via the Mixability Gap. ALT (2012)
Wojciech Kotlowski, Peter Grünwald
Sequential normalized maximum likelihood in log-loss prediction. ITW (2012)
Peter Grünwald
Commentary on "The Optimality of Jeffreys Prior for Online Density Estimation and the Asymptotic Normality of Maximum Likelihood Estimators". COLT (2012)
Peter Grünwald, John Smith Jones, Jane de Winter, Élouise Smith
Safe Learning: bridging the gap between Bayes, MDL and statistical learning theory via empirical convexity. COLT (2011)
Wojciech Kotlowski, Peter Grünwald
Maximum Likelihood vs. Sequential Normalized Maximum Likelihood in On-line Density Estimation. COLT (2011)
Wojciech Kotlowski, Peter Grünwald, Steven de Rooij
Following the Flattened Leader. COLT (2010)
Peter Grünwald, Wojciech Kotlowski
Prequential Plug-In Codes that Achieve Optimal Redundancy Rates even if the Model is Wrong CoRR (2010)
Peter Grünwald, Peter Harremoës
Finiteness of redundancy, regret, Shtarkov sums, and Jeffreys integrals in exponential families. ISIT (2009)
Peter Grünwald, Joseph Y. Halpern
A Game-Theoretic Analysis of Updating Sets of Probabilities. UAI (2008)
Tim van Erven, Peter Grünwald, Steven de Rooij
Catching Up Faster by Switching Sooner: A Prequential Solution to the AIC-BIC Dilemma CoRR (2008)
Peter Grünwald, John Langford
Suboptimal behavior of Bayes and MDL in classification under misspecification. Mach. Learn. 66 (2-3) (2007)
Peter Grünwald
Springer (2005), ISBN 038723795X 432 pp, Hardbound. Comput. J. 50 (3) (2007)
Steven de Rooij, Peter Grünwald
MDL model selection using the ML plug-in code. ISIT (2005)
Peter Grünwald, Steven de Rooij
Asymptotic Log-Loss of Prequential Maximum Likelihood Codes. COLT (2005)
Steven de Rooij, Peter Grünwald
An Empirical Study of MDL Model Selection with Infinite Parametric Complexity CoRR (2005)
Teemu Roos, Peter Grünwald, Petri Myllymäki, Henry Tirri
Generalization to Unseen Cases. NIPS (2005)
Peter Grünwald, Steven de Rooij
Asymptotic Log-loss of Prequential Maximum Likelihood Codes CoRR (2005)
Wim van Dam, Richard D. Gill, Peter Grünwald
The statistical strength of nonlocality proofs. IEEE Trans. Inf. Theory 51 (8) (2005)
Teemu Roos, Hannes Wettig, Peter Grünwald, Petri Myllymäki, Henry Tirri
On Discriminative Bayesian Network Classifiers and Logistic Regression. Mach. Learn. 59 (3) (2005)
Teemu Roos, Peter Grünwald, Petri Myllymäki, Henry Tirri
Generalization to Unseen Cases. BNAIC (2005)
Peter Grünwald, Paul M. B. Vitányi
Shannon Information and Kolmogorov Complexity CoRR (2004)
Peter Grünwald, John Langford
Suboptimal behaviour of Bayes and MDL in classification under misspecification CoRR (2004)
Peter Grünwald, John Langford
Suboptimal Behavior of Bayes and MDL in Classification Under Misspecification. COLT (2004)
Peter Grünwald
A tutorial introduction to the minimum description length principle CoRR (2004)
Peter Grünwald, Joseph Y. Halpern
When Ignorance is Bliss. UAI (2004)
Peter Grünwald, Joseph Y. Halpern
Updating Probabilities. J. Artif. Intell. Res. 19 (2003)
Peter Grünwald, Joseph Y. Halpern
Updating Probabilities CoRR (2003)
Peter Grünwald
A Minimum Descriptipn Length Approach to Grammar Inference. ECML Workshop on Learning Contex-Free Grammars (2003)
Peter Grünwald, Paul M. B. Vitányi
Kolmogorov Complexity and Information Theory. With an Interpretation in Terms of Questions and Answers. J. Log. Lang. Inf. 12 (4) (2003)
Hannes Wettig, Peter Grünwald, Teemu Roos, Petri Myllymäki, Henry Tirri
When Discriminative Learning of Bayesian Network Parameters Is Easy. IJCAI (2003)
Peter Grünwald, Joseph Y. Halpern
Updating Probabilities. UAI (2002)
Peter Grünwald
Strong Entropy Concentration, Game Theory, and Algorithmic Randomness. COLT/EuroCOLT (2001)
Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri, Peter Grünwald
On predictive distributions and Bayesian networks. Stat. Comput. 10 (1) (2000)
Peter Grünwald
Maximum Entropy and the Glasses You are Looking Through. UAI (2000)
Peter Grünwald
Viewing all Models as "Probabilistic". COLT (1999)
Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri, Peter Grünwald
Bayesian and Information-Theories Priors for Bayesian Network Parameters. ECML (1998)
Peter Grünwald, Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri
Minimum Encoding Approaches for Predictive Modeling. UAI (1998)
Peter Grünwald
Causation and Nonmonotonic Temporal Reasoning. KI (1997)
Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri, Peter Grünwald
Comparing Predictive Inference Methods for Discrete Domains. AISTATS (1997)
Peter Grünwald
A minimum description length approach to grammar inference. Learning for Natural Language Processing (1995)