Peter Grünwald
14 papers · 2007–2023 · 4 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (26) 🏃 Academic Marathon · Full 🌍 Conference Polyglot · Bronze 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird
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Keyword Champion
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Keyword Pioneer
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Trend Setter
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Unstoppable · Bronze
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Conference Pioneer
💎
Century Club · Bronze
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Keyword Collector
(78)
Venues
Top co-authors
Research topics
Machine Learning
(13)
Optimization & Theory
(13)
Mathematics & Optimization
(6)
Artificial Intelligence
(4)
Learning Types
(4)
Bayesian & Probabilistic · Artificial Intelligence
(3)
Optimization
(3)
Statistics
(3)
Bayesian & Probabilistic · Machine Learning
(2)
Core Methods
(2)
Mathematics
(2)
Core AI
(1)
Probability
(1)
Keywords
learning rate
(4)
regret bound
(4)
online learning
(3)
fast rate
(3)
bernstein condition
(3)
sequential normalized maximum likelihood
(2)
generalization bound
(2)
exponential family
(2)
minimum description length
(2)
convergence rate
(2)
model selection
(1)
regret minimization
(1)
maximum likelihood
(1)
cross validation
(1)
hedge algorithm
(1)
statistical consistency
(1)
causal inference
(1)
statistical learning theory
(1)
bayesian model averaging
(1)
bayesian inference
(1)
Papers
Minimax Risk Classifiers with 0-1 Loss
JMLR 2023
Safe Sequential Testing and Effect Estimation in Stratified Count Data
AISTATS 2023
PAC-Bayes, MAC-Bayes and Conditional Mutual Information: Fast rate bounds that handle general VC classes
COLT 2021
Safe-Bayesian Generalized Linear Regression
AISTATS 2020
PAC-Bayes Un-Expected Bernstein Inequality
NeurIPS 2019
Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning
NeurIPS 2016
Conference on Learning Theory 2015: Preface
COLT 2015
Learning the Learning Rate for Prediction with Expert Advice
NeurIPS 2014
Horizon-Independent Optimal Prediction with Log-Loss in Exponential Families
COLT 2013
Mixability in Statistical Learning
NeurIPS 2012
Adaptive Hedge
NeurIPS 2011
Maximum Likelihood vs. Sequential Normalized Maximum Likelihood in On-line Density Estimation
COLT 2011
Safe Learning: bridging the gap between Bayes, MDL and statistical learning theory via empirical convexity
COLT 2011
Catching Up Faster in Bayesian Model Selection and Model Averaging
NeurIPS 2007