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Peter Grünwald
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- affiliation: National Research Institute for Mathematics and Computer Science, Amsterdam, Netherlands
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2020 – today
- 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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