I am a PhD candidate at CWI under supervision of Peter Grünwald. I work on problems and solutions in the intersection of machine learning and statistics where the model or data collection process is misspecified, with a focus on hypothesis testing and sequential learning. At the moment I'm working on a general framework for hypothesis testing with Wouter Koolen and Peter Grünwald, and Bayesian inference under model misspecification with Peter Grünwald. I'm also interested in the mathematical and philosophical foundations of Bayesianism, machine learning, statistics and probability theory, and I'm working with Tom Sterkenburg on the foundations of Bayesian inference. Until January 2019 worked one day a week at Leiden University with Jacqueline Meulman as coordinator of the MSc programme Statistical Science.
From April - July 2019 I will visit SequeL (Inria Lille) on a LUF travel grant.
Rianne de Heide
Machine Learning Group, CWI
Science Park 123, Amsterdam
heide at cwi dot nl
Statistical Science Group, Mathematical Institute - Leiden University
Writings
Publications
Invited discussion to the paper Using Stacking to Average Bayesian Predictive Distributions by Yao, Vehtari, Simpson and Gelman
Peter Grünwald and Rianne de Heide
Bayesian Analysis 13 (2018), no. 3, 917-1003.
Preprints
On the truth-convergence of open-minded Bayesianism
Tom F. Sterkenburg and Rianne de Heide
Preliminary version available on request.
Optional Stopping with Bayes Factors: a categorization and extension of folklore results, with an application to invariant situations
Allard Hendriksen, Rianne de Heide and Peter Grünwald
arXiv 1807.09077, 2018
Why optional stopping is a problem for Bayesians
Rianne de Heide and Peter Grünwald
arXiv 1708.08278, 2018
Other
The Safe-Bayesian Lasso (MSc Thesis)
Rianne de Heide, 2016
Teaching
Upcoming/current teaching as a lecturer
- Machine Learning Theory (MasterMath, the joint universities national Dutch Master's Programme in Mathematics), Fall 2018
together with Wouter Koolen and Peter Grünwald. I do the first half on Statistical Learning Theory.
Past teaching as a lecturer
- Lectures on online learning and bandits in Peter Grünwald's Information Theoretic Learning course (MSc Mathematics, Leiden University), Spring 2018
- Lecture on Information Theory in Machine Learning in Christian Schaffner's Information Theory course (MSc Logic, University of Amsterdam), Fall 2017
- Machine Learning Theory (MasterMath, the joint universities national Dutch Master's Programme in Mathematics), Fall 2017
together with Wouter Koolen and Peter Grünwald. I did the first half on Statistical Learning Theory. - Lecture on online learning in Peter Grünwald's Information Theoretic Learning course (MSc Mathematics, Leiden University), Spring 2017
Past teaching as an assistant
- Information Theoretic Learning (MSc Mathematics, Leiden University), Spring 2018
- Information Theoretic Learning (MSc Mathematics, Leiden University), Spring 2017
- Mathematics for Statisticians (MSc Statistical Science, Leiden University), Fall 2015
- Mathematics for Statisticians (MSc Statistical Science, Leiden University), Fall 2014
- Mathematics for Statisticians (MSc Statistical Science, Leiden University), Fall 2013
Background
I obtained a BSc in Mathematics from the University of Groningen and a MSc in Mathematics cum laude from Leiden University. I also hold a Bachelor of Music from the Prins Claus Conservatoire and a Master of Music from the Royal Conservatory of The Hague, both in Classical music - Horn.Other
- Software
- R Package SafeBayes
- Miscellaneous
- Saint Nicholas, Rooks and Graph Matchings
- Distractions
- I like cycling, learning languages and classical singing. I'm a contralto, and sing in the VU-Kamerkoor and many side-projects.