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, with a focus on hypothesis testing and sequential learning. At the moment I'm working on a new framework for hypothesis testing with Wouter Koolen and Peter Grünwald, and Bayesian inference under model misspecification with Peter Grünwald and Alisa Kirichenko. 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.
I'm a board member of the European Women in Mathematics – The Netherlands, the Dutch association of women professional mathematicians.
In spring 2019, I visited SequeL ( Inria Lille-Nord Europe) on a LUF travel grant, to work with Emilie Kaufmann and Michal Valko.
Rianne de Heide
Machine Learning Group, CWI
Science Park 123, Amsterdam
heide at cwi dot nl
Statistical Science Group, Mathematical Institute - Leiden University
Papers
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
Fixed-Confidence Guarantees for Bayesian Best-Arm Identification
Xuedong Shang, Rianne de Heide, Emilie Kaufman, Pierre Ménard and Michal Valko
HAL-02330187, arXiv 1910.10945, 2019; Accepted to AISTATS 2020
Safe-Bayesian Generalized Linear Regression
Rianne de Heide, Alisa Kirichenko, Nishant Mehta and Peter Grünwald
arXiv 1910.09227, 2019; Accepted to AISTATS 2020
Safe Testing
Peter Grünwald, Rianne de Heide and Wouter Koolen
arXiv 1906.07801, 2019
The truth-convergence of open-minded Bayesianism
Tom F. Sterkenburg and Rianne de Heide
Submitted. Preliminary version available on request. 2019
Accepted to the Formal Epistemology Workshop 2019 (60 minutes talk, commentary and discussion), and the biennial conference of the European Philosophy of Science Association.
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. Submitted.
Why optional stopping is a problem for Bayesians
Rianne de Heide and Peter Grünwald
arXiv 1708.08278, 2018. Submitted.
Other
The Safe-Bayesian Lasso (MSc Thesis)
Rianne de Heide, 2016
Selected Talks
- AI seminar, University of Alberta, February 2020
tbk - Stochastics seminar, Otto von Güricke Universität Magdeburg, November 2019
Safe Testing - Google DeepMind, Paris, July 2019
Safe Testing - Sequel Seminar, Inria Lille, June 2019
Safe Testing - Formal Epistemology Workshop , Turin, June 2019
On the truth-convergence of open-minded Bayesianism - Scientific Meeting, CWI Amsterdam, April 2018
Hypothesis Testing
Teaching
Past teaching as a lecturer
- Machine Learning Theory (MasterMath, the joint universities national Dutch Master's Programme in Mathematics), Fall 2019
together with Wouter Koolen and Peter Grünwald. I did the first half on Statistical Learning Theory. - Machine Learning Theory (MasterMath, the joint universities national Dutch Master's Programme in Mathematics), Fall 2018
together with Wouter Koolen and Peter Grünwald. I did the first half on Statistical Learning Theory. - 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 2017, 2018
- Mathematics for Statisticians (MSc Statistical Science, Leiden University), Fall 2013, 2014, 2015
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.Until January 2019 worked one day a week at Leiden University with Jacqueline Meulman as coordinator of the MSc programme Statistical Science.
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.