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ORCIDPeter Grünwald
Peter D. Grünwald – Peter Grunwald
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- affiliation: National Research Institute for Mathematics and Computer Science, Amsterdam, Netherlands
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2020 – today
- 2024
[j18]Tyron Lardy, Peter Grünwald, Peter Harremoës:
Reverse Information Projections and Optimal E-Statistics. IEEE Trans. Inf. Theory 70(11): 7616-7631 (2024)- [p1]Jamila Alsayed Kassem, Corinne G. Allaart, Saba Amiri, Milen G. Kebede, Tim Müller, Rosanne Turner, Adam Belloum, L. Thomas van Binsbergen, Peter Grunwald, Aart van Halteren, Paola Grosso, Cees de Laat, Sander Klous:
Building a Digital Health Twin for Personalized Intervention: The EPI Project. Commit2Data 2024: 2:1-2:18 - 2023
- [j17]Santiago Mazuelas, Mauricio Romero, Peter Grunwald:
Minimax Risk Classifiers with 0-1 Loss. J. Mach. Learn. Res. 24: 208:1-208:48 (2023) - [c49]Rosanne Turner, Peter Grunwald:
Safe Sequential Testing and Effect Estimation in Stratified Count Data. AISTATS 2023: 4880-4893 - [c48]Peter Harremoës, Tyron Lardy, Peter Grünwald:
Universal Reverse Information Projections and Optimal E-statistics. ISIT 2023: 394-399 - [i40]Peter Harremoës, Tyron Lardy, Peter Grünwald:
Universal Reverse Information Projections and Optimal E-statistics. CoRR abs/2306.16646 (2023) - 2022
- [j16]Hugo Manuel Proença
, Peter Grünwald, Thomas Bäck, Matthijs van Leeuwen:
Robust subgroup discovery. Data Min. Knowl. Discov. 36(5): 1885-1970 (2022) - [j15]Wouter M. Koolen, Peter Grünwald:
Log-optimal anytime-valid E-values. Int. J. Approx. Reason. 141: 69-82 (2022) - [i39]Santiago Mazuelas, Mauricio Romero, Peter Grünwald:
Minimax risk classifiers with 0-1 loss. CoRR abs/2201.06487 (2022) - [i38]Tom F. Sterkenburg, Peter D. Grünwald:
The no-free-lunch theorems of supervised learning. CoRR abs/2202.04513 (2022) - [i37]Aaditya Ramdas, Peter Grünwald, Vladimir Vovk, Glenn Shafer:
Game-theoretic statistics and safe anytime-valid inference. CoRR abs/2210.01948 (2022) - 2021
- [c47]Peter Grünwald, Thomas Steinke, Lydia Zakynthinou:
PAC-Bayes, MAC-Bayes and Conditional Mutual Information: Fast rate bounds that handle general VC classes. COLT 2021: 2217-2247 - [c46]Peter Grünwald, Alexander Ly, Muriel Felipe Pérez-Ortiz, Judith Ter Schure:
The Safe Logrank Test: Error Control under Optional Stopping, Continuation and Prior Misspecification. SPACA 2021: 107-117 - [i36]Rosanne Turner, Alexander Ly, Peter Grünwald:
Safe Tests and Always-Valid Confidence Intervals for contingency tables and beyond. CoRR abs/2106.02693 (2021) - [i35]Peter Grünwald, Thomas Steinke, Lydia Zakynthinou:
PAC-Bayes, MAC-Bayes and Conditional Mutual Information: Fast rate bounds that handle general VC classes. CoRR abs/2106.09683 (2021) - 2020
- [j14]Peter D. Grünwald, Nishant A. Mehta:
Fast Rates for General Unbounded Loss Functions: From ERM to Generalized Bayes. J. Mach. Learn. Res. 21: 56:1-56:80 (2020) - [c45]Rianne de Heide, Alisa Kirichenko, Peter Grunwald, Nishant A. Mehta:
Safe-Bayesian Generalized Linear Regression. AISTATS 2020: 2623-2633 - [c44]Peter Grünwald, Rianne de Heide, Wouter M. Koolen:
Safe Testing. ITA 2020: 1-54 - [c43]Hugo Manuel Proença, Peter Grünwald, Thomas Bäck, Matthijs van Leeuwen:
Discovering Outstanding Subgroup Lists for Numeric Targets Using MDL. ECML/PKDD (1) 2020: 19-35 - [i34]Hugo Manuel Proença, Peter Grünwald, Thomas Bäck, Matthijs van Leeuwen:
Discovering outstanding subgroup lists for numeric targets using MDL. CoRR abs/2006.09186 (2020)
2010 – 2019
- 2019
- [c42]Peter D. Grünwald, Nishant A. Mehta:
A tight excess risk bound via a unified PAC-Bayesian-Rademacher-Shtarkov-MDL complexity. ALT 2019: 433-465 - [c41]Thijs van Ommen, Wouter M. Koolen, Peter D. Grünwald:
Efficient Algorithms for Minimax Decisions Under Tree-Structured Incompleteness. ECSQARU 2019: 336-347 - [c40]Zakaria Mhammedi, Peter Grünwald, Benjamin Guedj:
PAC-Bayes Un-Expected Bernstein Inequality. NeurIPS 2019: 12180-12191 - [i33]Zakaria Mhammedi, Peter D. Grünwald, Benjamin Guedj:
PAC-Bayes Un-Expected Bernstein Inequality. CoRR abs/1905.13367 (2019) - [i32]Peter Grünwald, Rianne de Heide, Wouter M. Koolen:
Safe Testing. CoRR abs/1906.07801 (2019) - [i31]Peter Grünwald, Teemu Roos:
Minimum Description Length Revisited. CoRR abs/1908.08484 (2019) - [i30]Rianne de Heide, Alisa Kirichenko, Nishant A. Mehta, Peter Grünwald:
Safe-Bayesian Generalized Linear Regression. CoRR abs/1910.09227 (2019) - 2018
- [i29]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 abs/1807.09077 (2018) - 2017
- [i28]Peter D. Grünwald, Nishant A. Mehta:
A Tight Excess Risk Bound via a Unified PAC-Bayesian-Rademacher-Shtarkov-MDL Complexity. CoRR abs/1710.07732 (2017) - 2016
- [j13]Thijs van Ommen, Wouter M. Koolen, Thijs E. Feenstra, Peter D. Grünwald:
Robust probability updating. Int. J. Approx. Reason. 74: 30-57 (2016) - [j12]Kostas N. Oikonomou, Peter D. Grünwald:
Explicit Bounds for Entropy Concentration Under Linear Constraints. IEEE Trans. Inf. Theory 62(3): 1206-1230 (2016) - [c39]Wouter M. Koolen, Peter Grünwald, Tim van Erven:
Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning. NIPS 2016: 4457-4465 - [i27]Peter Grünwald:
Safe Probability. CoRR abs/1604.01785 (2016) - [i26]Peter D. Grünwald, Nishant A. Mehta:
Fast Rates with Unbounded Losses. CoRR abs/1605.00252 (2016) - [i25]Wouter M. Koolen, Peter Grünwald, Tim van Erven:
Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning. CoRR abs/1605.06439 (2016) - 2015
- [j11]Tim van Erven, Peter D. Grünwald, Nishant A. Mehta, Mark D. Reid, Robert C. Williamson:
Fast rates in statistical and online learning. J. Mach. Learn. Res. 16: 1793-1861 (2015) - [c38]Peter Grünwald, Elad Hazan:
Conference on Learning Theory 2015: Preface. COLT 2015: 1-3 - [e2]Peter Grünwald, Elad Hazan, Satyen Kale:
Proceedings of The 28th Conference on Learning Theory, COLT 2015, Paris, France, July 3-6, 2015. JMLR Workshop and Conference Proceedings 40, JMLR.org 2015 [contents] - [i24]Tim van Erven, Peter D. Grünwald, Nishant A. Mehta, Mark D. Reid, Robert C. Williamson:
Fast rates in statistical and online learning. CoRR abs/1507.02592 (2015) - [i23]Thijs van Ommen, Wouter M. Koolen, Thijs E. Feenstra, Peter D. Grünwald:
Worst-case Optimal Probability Updating. CoRR abs/1512.03223 (2015) - 2014
- [j10]Steven de Rooij, Tim van Erven, Peter D. Grünwald, Wouter M. Koolen:
Follow the leader if you can, hedge if you must. J. Mach. Learn. Res. 15(1): 1281-1316 (2014) - [c37]Jouke Witteveen, Wouter Duivesteijn, Arno J. Knobbe, Peter Grünwald:
RealKrimp - Finding Hyperintervals that Compress with MDL for Real-Valued Data. IDA 2014: 368-379 - [c36]Wouter M. Koolen, Tim van Erven, Peter Grünwald:
Learning the Learning Rate for Prediction with Expert Advice. NIPS 2014: 2294-2302 - [i22]Peter D. Grünwald, Joseph Y. Halpern:
Making Decisions Using Sets of Probabilities: Updating, Time Consistency, and Calibration. CoRR abs/1401.3906 (2014) - [i21]Peter D. Grünwald, Joseph Y. Halpern:
Updating Probabilities. CoRR abs/1407.7183 (2014) - [i20]Peter D. Grünwald, Joseph Y. Halpern:
When Ignorance is Bliss. CoRR abs/1407.7188 (2014) - [i19]Peter D. Grünwald, Joseph Y. Halpern:
A Game-Theoretic Analysis of Updating Sets of Probabilities. CoRR abs/1407.7190 (2014) - 2013
- [c35]Peter L. Bartlett, Peter Grünwald, Peter Harremoës, Fares Hedayati, Wojciech Kotlowski:
Horizon-Independent Optimal Prediction with Log-Loss in Exponential Families. COLT 2013: 639-661 - [c34]Peter Grünwald:
Safe Probability: Restricted Conditioning and Extended Marginalization. ECSQARU 2013: 242-253 - [i18]Steven de Rooij, Tim van Erven, Peter D. Grünwald, Wouter M. Koolen:
Follow the Leader If You Can, Hedge If You Must. CoRR abs/1301.0534 (2013) - [i17]Peter D. Grünwald:
Maximum Entropy and the Glasses You Are Looking Through. CoRR abs/1301.3860 (2013) - [i16]Peter Grünwald, Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri:
Minimum Encoding Approaches for Predictive Modeling. CoRR abs/1301.7378 (2013) - [i15]Peter L. Bartlett, Peter Grunwald, Peter Harremoës, Fares Hedayati, Wojciech Kotlowski:
Horizon-Independent Optimal Prediction with Log-Loss in Exponential Families. CoRR abs/1305.4324 (2013) - 2012
- [c33]Peter Grünwald:
The Safe Bayesian - Learning the Learning Rate via the Mixability Gap. ALT 2012: 169-183 - [c32]Wojciech Kotlowski, Peter Grünwald:
Sequential normalized maximum likelihood in log-loss prediction. ITW 2012: 547-551 - [c31]Tim van Erven, Peter D. Grünwald, Mark D. Reid, Robert C. Williamson:
Mixability in Statistical Learning. NIPS 2012: 1700-1708 - [c30]Peter Grünwald:
Commentary on "The Optimality of Jeffreys Prior for Online Density Estimation and the Asymptotic Normality of Maximum Likelihood Estimators". COLT 2012: 7.14-7.17 - [i14]Peter Grunwald, Peter Spirtes:
Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence (2010). CoRR abs/1205.2597 (2012) - 2011
- [j9]Peter D. Grünwald, Joseph Y. Halpern:
Making Decisions Using Sets of Probabilities: Updating, Time Consistency, and Calibration. J. Artif. Intell. Res. 42: 393-426 (2011) - [c29]Tim van Erven, Peter Grunwald, Wouter M. Koolen, Steven de Rooij:
Adaptive Hedge. NIPS 2011: 1656-1664 - [c28]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: 397-420 - [c27]Wojciech Kotlowski, Peter Grünwald:
Maximum Likelihood vs. Sequential Normalized Maximum Likelihood in On-line Density Estimation. COLT 2011: 457-476 - [c26]Peter D. Grünwald, Wojciech Kotlowski:
Bounds on Individual Risk for Log-loss Predictors. COLT 2011: 813-816 - 2010
- [c25]Wojciech Kotlowski, Peter Grünwald, Steven de Rooij:
Following the Flattened Leader. COLT 2010: 106-118 - [c24]Peter Grunwald, Wojciech Kotlowski:
Prequential plug-in codes that achieve optimal redundancy rates even if the model is wrong. ISIT 2010: 1383-1387 - [e1]Peter Grünwald, Peter Spirtes:
UAI 2010, Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence, Catalina Island, CA, USA, July 8-11, 2010. AUAI Press 2010, ISBN 978-0-9749039-6-5 [contents] - [i13]Peter Grünwald, Wojciech Kotlowski:
Prequential Plug-In Codes that Achieve Optimal Redundancy Rates even if the Model is Wrong. CoRR abs/1002.0757 (2010)
2000 – 2009
- 2009
- [c23]Peter Grünwald, Peter Harremoës:
Finiteness of redundancy, regret, Shtarkov sums, and Jeffreys integrals in exponential families. ISIT 2009: 714-718 - [i12]Peter Grunwald, Peter Harremoës:
Regret and Jeffreys Integrals in Exp. Families. CoRR abs/0903.5399 (2009) - 2008
- [c22]Peter Grunwald:
The Catch-Up Phenomenon in Bayesian Inference. COLT 2008: 1-2 - [c21]Peter Grunwald, Steven de Rooij, Tim van Erven:
The Catch-Up Phenomenon. ITW 2008: 259-260 - [c20]Peter Grünwald, Joseph Y. Halpern:
A Game-Theoretic Analysis of Updating Sets of Probabilities. UAI 2008: 240-247 - [i11]Tim van Erven, Peter Grünwald, Steven de Rooij:
Catching Up Faster by Switching Sooner: A Prequential Solution to the AIC-BIC Dilemma. CoRR abs/0807.1005 (2008) - [i10]Peter Grunwald:
Entropy Concentration and the Empirical Coding Game. CoRR abs/0809.1017 (2008) - [i9]Peter D. Grünwald, Paul M. B. Vitányi:
Algorithmic information theory. CoRR abs/0809.2754 (2008) - 2007
- [j8]Peter Grünwald:
Christopher S. Wallace Statistical and Inductive Inference by Minimum Message Length. Springer (2005), ISBN 038723795X 432 pp, Hardbound. Comput. J. 50(3): 369-370 (2007) - [j7]Jorma Rissanen, Peter D. Grünwald, Jukka Heikkonen, Petri Myllymäki, Teemu Roos, Juho Rousu:
Information Theoretic Methods for Bioinformatics. EURASIP J. Bioinform. Syst. Biol. 2007 (2007) - [j6]Peter Grünwald, John Langford:
Suboptimal behavior of Bayes and MDL in classification under misspecification. Mach. Learn. 66(2-3): 119-149 (2007) - [c19]Tim van Erven, Peter Grunwald, Steven de Rooij:
Catching Up Faster in Bayesian Model Selection and Model Averaging. NIPS 2007: 417-424 - [i8]Peter D. Grünwald, Joseph Y. Halpern:
A Game-Theoretic Analysis of Updating Sets of Probabilities. CoRR abs/0711.3235 (2007) - 2005
- [j5]Teemu Roos, Hannes Wettig, Peter Grünwald, Petri Myllymäki, Henry Tirri:
On Discriminative Bayesian Network Classifiers and Logistic Regression. Mach. Learn. 59(3): 267-296 (2005) - [j4]Wim van Dam, Richard D. Gill, Peter Grünwald:
The statistical strength of nonlocality proofs. IEEE Trans. Inf. Theory 51(8): 2812-2835 (2005) - [c18]Teemu Roos, Peter Grünwald, Petri Myllymäki, Henry Tirri:
Generalization to Unseen Cases. BNAIC 2005: 194-201 - [c17]Peter Grünwald, Steven de Rooij:
Asymptotic Log-Loss of Prequential Maximum Likelihood Codes. COLT 2005: 652-667 - [c16]Steven de Rooij, Peter Grünwald:
MDL model selection using the ML plug-in code. ISIT 2005: 760-764 - [c15]Teemu Roos, Peter Grünwald, Petri Myllymäki, Henry Tirri:
Generalization to Unseen Cases. NIPS 2005: 1129-1136 - [i7]Steven de Rooij, Peter Grünwald:
An Empirical Study of MDL Model Selection with Infinite Parametric Complexity. CoRR abs/cs/0501028 (2005) - [i6]Peter Grünwald, Steven de Rooij:
Asymptotic Log-loss of Prequential Maximum Likelihood Codes. CoRR abs/cs/0502004 (2005) - [i5]Peter D. Grünwald, Joseph Y. Halpern:
When Ignorance is Bliss. CoRR abs/cs/0510080 (2005) - 2004
- [c14]Peter Grünwald, John Langford:
Suboptimal Behavior of Bayes and MDL in Classification Under Misspecification. COLT 2004: 331-347 - [c13]Peter Grünwald, Joseph Y. Halpern:
When Ignorance is Bliss. UAI 2004: 226-234 - [i4]Peter Grünwald, Paul M. B. Vitányi:
Shannon Information and Kolmogorov Complexity. CoRR cs.IT/0410002 (2004) - [i3]Peter Grünwald:
A tutorial introduction to the minimum description length principle. CoRR math.ST/0406077 (2004) - [i2]Peter Grünwald, John Langford:
Suboptimal behaviour of Bayes and MDL in classification under misspecification. CoRR math.ST/0406221 (2004) - 2003
- [j3]Peter Grünwald, Joseph Y. Halpern:
Updating Probabilities. J. Artif. Intell. Res. 19: 243-278 (2003) - [j2]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): 497-529 (2003) - [c12]Peter Grünwald:
A Minimum Descriptipn Length Approach to Grammar Inference. ECML Workshop on Learning Contex-Free Grammars 2003 - [c11]Hannes Wettig, Peter Grünwald, Teemu Roos, Petri Myllymäki, Henry Tirri:
When Discriminative Learning of Bayesian Network Parameters Is Easy. IJCAI 2003: 491-498 - [i1]Peter Grünwald, Joseph Y. Halpern:
Updating Probabilities. CoRR cs.AI/0306124 (2003) - 2002
- [c10]Peter D. Grünwald, A. Philip Dawid:
Game theory, maximum generalized entropy, minimum discrepancy, robust Bayes and Pythagoras. ITW 2002: 94-97 - [c9]Peter Grünwald, Joseph Y. Halpern:
Updating Probabilities. UAI 2002: 187-196 - 2001
- [c8]Peter Grünwald:
Strong Entropy Concentration, Game Theory, and Algorithmic Randomness. COLT/EuroCOLT 2001: 320-336 - 2000
- [j1]Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri, Peter Grünwald:
On predictive distributions and Bayesian networks. Stat. Comput. 10(1): 39-54 (2000) - [c7]Peter Grünwald:
Maximum Entropy and the Glasses You are Looking Through. UAI 2000: 238-246
1990 – 1999
- 1999
- [c6]Peter Grünwald:
Viewing all Models as "Probabilistic". COLT 1999: 171-182 - 1998
- [c5]Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri, Peter Grünwald:
Bayesian and Information-Theories Priors for Bayesian Network Parameters. ECML 1998: 89-94 - [c4]Peter Grünwald, Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri:
Minimum Encoding Approaches for Predictive Modeling. UAI 1998: 183-192 - 1997
- [c3]Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri, Peter Grünwald:
Comparing Predictive Inference Methods for Discrete Domains. AISTATS 1997: 311-318 - [c2]Peter Grünwald:
Causation and Nonmonotonic Temporal Reasoning. KI 1997: 159-170 - 1995
- [c1]Peter Grünwald:
A minimum description length approach to grammar inference. Learning for Natural Language Processing 1995: 203-216
Coauthor Index
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