Peter Grünwald

72 papers A* 13A 7B 6C 1Misc 2Journal 33Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	On admissibility in post-hoc hypothesis testing. Int. J. Approx. Reason. Ben Chugg, Tyron Lardy, Aaditya Ramdas, Peter Grünwald
2024	J	`jnl`	Growth-Optimal E-Variables and an extension to the multivariate Csiszár-Sanov-Chernoff Theorem. CoRR Peter Grünwald, Yunda Hao, Akshay Balsubramani
2024	J	`jnl`	Reverse Information Projections and Optimal E-Statistics. IEEE Trans. Inf. Theory Tyron Lardy, Peter Grünwald, Peter Harremoës
2023	B	`conf`	Universal Reverse Information Projections and Optimal E-statistics. ISIT Peter Harremoës, Tyron Lardy, Peter Grünwald
2023	J	`jnl`	Universal Reverse Information Projections and Optimal E-statistics. CoRR Peter Harremoës, Tyron Lardy, Peter Grünwald
2022	J	`jnl`	Game-theoretic statistics and safe anytime-valid inference. CoRR Aaditya Ramdas, Peter Grünwald, Vladimir Vovk, Glenn Shafer
2022	J	`jnl`	Log-optimal anytime-valid E-values. Int. J. Approx. Reason. Wouter M. Koolen, Peter Grünwald
2022	J	`jnl`	Minimax risk classifiers with 0-1 loss. CoRR Santiago Mazuelas, Mauricio Romero, Peter Grünwald
2022	J	`jnl`	Robust subgroup discovery. Data Min. Knowl. Discov. Hugo Manuel Proença, Peter Grünwald, Thomas Bäck, Matthijs van Leeuwen
2021	A*	`conf`	PAC-Bayes, MAC-Bayes and Conditional Mutual Information: Fast rate bounds that handle general VC classes. COLT Peter Grünwald, Thomas Steinke, Lydia Zakynthinou
2021	J	`jnl`	PAC-Bayes, MAC-Bayes and Conditional Mutual Information: Fast rate bounds that handle general VC classes. CoRR Peter Grünwald, Thomas Steinke, Lydia Zakynthinou
2021	J	`jnl`	Safe Tests and Always-Valid Confidence Intervals for contingency tables and beyond. CoRR Rosanne Turner, Alexander Ly, Peter Grünwald
2021	—	`conf`	The Safe Logrank Test: Error Control under Optional Stopping, Continuation and Prior Misspecification. SPACA Peter Grünwald, Alexander Ly, Muriel Felipe Pérez-Ortiz, Judith ier Schure
2020	—	`conf`	Discovering Outstanding Subgroup Lists for Numeric Targets Using MDL. ECML/PKDD (1) Hugo Manuel Proença, Peter Grünwald, Thomas Bäck, Matthijs van Leeuwen
2020	J	`jnl`	Discovering outstanding subgroup lists for numeric targets using MDL. CoRR Hugo Manuel Proença, Peter Grünwald, Thomas Bäck, Matthijs van Leeuwen
2020	Misc	`conf`	Safe Testing. ITA Peter Grünwald, Rianne de Heide, Wouter M. Koolen
2019	J	`jnl`	Minimum Description Length Revisited. CoRR Peter Grünwald, Teemu Roos
2019	A*	`conf`	PAC-Bayes Un-Expected Bernstein Inequality. NeurIPS Zakaria Mhammedi, Peter Grünwald, Benjamin Guedj
2019	J	`jnl`	Safe Testing. CoRR Peter Grünwald, Rianne de Heide, Wouter M. Koolen
2019	J	`jnl`	Safe-Bayesian Generalized Linear Regression. CoRR Rianne de Heide, Alisa Kirichenko, Nishant A. Mehta, Peter Grünwald
2018	J	`jnl`	Optional Stopping with Bayes Factors: a categorization and extension of folklore results, with an application to invariant situations. CoRR Allard Hendriksen, Rianne de Heide, Peter Grünwald
2016	—	`conf`	Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning. NIPS Wouter M. Koolen, Peter Grünwald, Tim van Erven
2016	J	`jnl`	Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning. CoRR Wouter M. Koolen, Peter Grünwald, Tim van Erven
2016	J	`jnl`	Safe Probability. CoRR Peter Grünwald
2015	A*	`conf`	Conference on Learning Theory 2015: Preface. COLT Peter Grünwald, Elad Hazan
2015	A*	`ed.`	Proceedings of The 28th Conference on Learning Theory, COLT 2015, Paris, France, July 3-6, 2015 COLT Peter Grünwald, Elad Hazan, Satyen Kale
2014	—	`conf`	Learning the Learning Rate for Prediction with Expert Advice. NIPS Wouter M. Koolen, Tim van Erven, Peter Grünwald
2014	B	`conf`	RealKrimp - Finding Hyperintervals that Compress with MDL for Real-Valued Data. IDA Jouke Witteveen, Wouter Duivesteijn, Arno J. Knobbe, Peter Grünwald
2013	A*	`conf`	Horizon-Independent Optimal Prediction with Log-Loss in Exponential Families. COLT Peter L. Bartlett, Peter Grünwald, Peter Harremoës, Fares Hedayati, Wojciech Kotlowski
2013	J	`jnl`	Minimum Encoding Approaches for Predictive Modeling CoRR Peter Grünwald, Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri
2013	C	`conf`	Safe Probability: Restricted Conditioning and Extended Marginalization. ECSQARU Peter Grünwald
2012	A*	`conf`	Commentary on "The Optimality of Jeffreys Prior for Online Density Estimation and the Asymptotic Normality of Maximum Likelihood Estimators". COLT Peter Grünwald
2012	B	`conf`	Sequential normalized maximum likelihood in log-loss prediction. ITW Wojciech Kotlowski, Peter Grünwald
2012	B	`conf`	The Safe Bayesian - Learning the Learning Rate via the Mixability Gap. ALT Peter Grünwald
2011	A*	`conf`	Maximum Likelihood vs. Sequential Normalized Maximum Likelihood in On-line Density Estimation. COLT Wojciech Kotlowski, Peter Grünwald
2011	A*	`conf`	Safe Learning: bridging the gap between Bayes, MDL and statistical learning theory via empirical convexity. COLT Peter Grünwald, John Smith Jones, Jane de Winter, Élouise Smith
2010	A*	`conf`	Following the Flattened Leader. COLT Wojciech Kotlowski, Peter Grünwald, Steven de Rooij
2010	J	`jnl`	Prequential Plug-In Codes that Achieve Optimal Redundancy Rates even if the Model is Wrong CoRR Peter Grünwald, Wojciech Kotlowski
2010	A	`ed.`	UAI 2010, Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence, Catalina Island, CA, USA, July 8-11, 2010 UAI Peter Grünwald, Peter Spirtes
2009	B	`conf`	Finiteness of redundancy, regret, Shtarkov sums, and Jeffreys integrals in exponential families. ISIT Peter Grünwald, Peter Harremoës
2008	A	`conf`	A Game-Theoretic Analysis of Updating Sets of Probabilities. UAI Peter Grünwald, Joseph Y. Halpern
2008	J	`jnl`	Catching Up Faster by Switching Sooner: A Prequential Solution to the AIC-BIC Dilemma CoRR Tim van Erven, Peter Grünwald, Steven de Rooij
2007	J	`jnl`	Christopher S. Wallace Comput. J. Peter Grünwald
2007	J	`jnl`	Suboptimal behavior of Bayes and MDL in classification under misspecification. Mach. Learn. Peter Grünwald, John Langford
2005	J	`jnl`	An Empirical Study of MDL Model Selection with Infinite Parametric Complexity CoRR Steven de Rooij, Peter Grünwald
2005	A*	`conf`	Asymptotic Log-Loss of Prequential Maximum Likelihood Codes. COLT Peter Grünwald, Steven de Rooij
2005	J	`jnl`	Asymptotic Log-loss of Prequential Maximum Likelihood Codes CoRR Peter Grünwald, Steven de Rooij
2005	—	`conf`	Generalization to Unseen Cases. BNAIC Teemu Roos, Peter Grünwald, Petri Myllymäki, Henry Tirri
2005	—	`conf`	Generalization to Unseen Cases. NIPS Teemu Roos, Peter Grünwald, Petri Myllymäki, Henry Tirri
2005	B	`conf`	MDL model selection using the ML plug-in code. ISIT Steven de Rooij, Peter Grünwald
2005	J	`jnl`	On Discriminative Bayesian Network Classifiers and Logistic Regression. Mach. Learn. Teemu Roos, Hannes Wettig, Peter Grünwald, Petri Myllymäki, Henry Tirri
2005	J	`jnl`	The statistical strength of nonlocality proofs. IEEE Trans. Inf. Theory Wim van Dam, Richard D. Gill, Peter Grünwald
2004	J	`jnl`	A tutorial introduction to the minimum description length principle CoRR Peter Grünwald
2004	J	`jnl`	Shannon Information and Kolmogorov Complexity CoRR Peter Grünwald, Paul M. B. Vitányi
2004	A*	`conf`	Suboptimal Behavior of Bayes and MDL in Classification Under Misspecification. COLT Peter Grünwald, John Langford
2004	J	`jnl`	Suboptimal behaviour of Bayes and MDL in classification under misspecification CoRR Peter Grünwald, John Langford
2004	A	`conf`	When Ignorance is Bliss. UAI Peter Grünwald, Joseph Y. Halpern
2003	—	`conf`	A Minimum Descriptipn Length Approach to Grammar Inference. ECML Workshop on Learning Contex-Free Grammars Peter Grünwald
2003	J	`jnl`	Kolmogorov Complexity and Information Theory. With an Interpretation in Terms of Questions and Answers. J. Log. Lang. Inf. Peter Grünwald, Paul M. B. Vitányi
2003	J	`jnl`	Updating Probabilities CoRR Peter Grünwald, Joseph Y. Halpern
2003	J	`jnl`	Updating Probabilities. J. Artif. Intell. Res. Peter Grünwald, Joseph Y. Halpern
2003	A*	`conf`	When Discriminative Learning of Bayesian Network Parameters Is Easy. IJCAI Hannes Wettig, Peter Grünwald, Teemu Roos, Petri Myllymäki, Henry Tirri
2002	A	`conf`	Updating Probabilities. UAI Peter Grünwald, Joseph Y. Halpern
2001	—	`conf`	Strong Entropy Concentration, Game Theory, and Algorithmic Randomness. COLT/EuroCOLT Peter Grünwald
2000	A	`conf`	Maximum Entropy and the Glasses You are Looking Through. UAI Peter Grünwald
2000	J	`jnl`	On predictive distributions and Bayesian networks. Stat. Comput. Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri, Peter Grünwald
1999	A*	`conf`	Viewing all Models as "Probabilistic". COLT Peter Grünwald
1998	—	`conf`	Bayesian and Information-Theories Priors for Bayesian Network Parameters. ECML Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri, Peter Grünwald
1998	A	`conf`	Minimum Encoding Approaches for Predictive Modeling. UAI Peter Grünwald, Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri
1997	Misc	`conf`	Causation and Nonmonotonic Temporal Reasoning. KI Peter Grünwald
1997	A	`conf`	Comparing Predictive Inference Methods for Discrete Domains. AISTATS Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri, Peter Grünwald
1995	—	`conf`	A minimum description length approach to grammar inference. Learning for Natural Language Processing Peter Grünwald