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06/29/2023
Universal Reverse Information Projections and Optimal E-statistics
Information projections have found many important applications in probab...
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03/01/2023
E-values for k-Sample Tests With Exponential Families
We develop and compare e-variables for testing whether k samples of data...
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01/03/2023
The E-Posterior
We develop a representation of a decision maker's uncertainty based on e...
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10/04/2022
Game-theoretic statistics and safe anytime-valid inference
Safe anytime-valid inference (SAVI) provides measures of statistical evi...
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09/26/2022
Anytime Valid Tests of Conditional Independence Under Model-X
We propose a sequential, anytime valid method to test the conditional in...
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08/16/2022
E-Statistics, Group Invariance and Anytime Valid Testing
We study worst-case growth-rate optimal (GROW) E-variables for hypothesi...
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05/02/2022
Beyond Neyman-Pearson
A standard practice in statistical hypothesis testing is to mention the ...
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03/18/2022
Anytime-valid Confidence Intervals for Contingency Tables and Beyond
E variables are tools for designing tests that keep their type-I error g...
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01/17/2022
Minimax risk classifiers with 0-1 loss
Supervised classification techniques use training samples to learn a cla...
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09/24/2021
ALL-IN meta-analysis: breathing life into living systematic reviews
Science is idolized as a cumulative process ("standing on the shoulders ...
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06/17/2021
PAC-Bayes, MAC-Bayes and Conditional Mutual Information: Fast rate bounds that handle general VC classes
We give a novel, unified derivation of conditional PAC-Bayesian and mutu...
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06/04/2021
Safe Tests and Always-Valid Confidence Intervals for contingency tables and beyond
We develop E variables for testing whether two data streams come from th...
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06/19/2020
Minimax rates without the fixed sample size assumption
We generalize the notion of minimax convergence rate. In contrast to the...
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06/16/2020
Discovering outstanding subgroup lists for numeric targets using MDL
The task of subgroup discovery (SD) is to find interpretable description...
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10/21/2019
Safe-Bayesian Generalized Linear Regression
We study generalized Bayesian inference under misspecification, i.e. whe...
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08/21/2019
Minimum Description Length Revisited
This is an up-to-date introduction to and overview of the Minimum Descri...
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06/18/2019
Safe Testing
We present a new theory of hypothesis testing. The main concept is the S...
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07/24/2018
Optional Stopping with Bayes Factors: a categorization and extension of folklore results, with an application to invariant situations
It is often claimed that Bayesian methods, in particular Bayes factor me...
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04/06/2016
Safe Probability
We formalize the idea of probability distributions that lead to reliable...
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05/19/2013
Horizon-Independent Optimal Prediction with Log-Loss in Exponential Families
We study online learning under logarithmic loss with regular parametric ...
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05/11/2012
Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence (2010)
This is the Proceedings of the Twenty-Sixth Conference on Uncertainty in...
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10/28/2011
Adaptive Hedge
Most methods for decision-theoretic online learning are based on the Hed...
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07/07/2008
