Rianne de Heide
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Machine Learning Group, Statistical Science Group |
About me
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.
Research
My research interests include
Bandits, pure exploration problems
(Sequential) hypothesis testing
Bayesian methods
Learning theory
Foundations of ML, stats and probability theory
Recent Publications
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 2020Safe-Bayesian Generalized Linear Regression
Rianne de Heide, Alisa Kirichenko, Nishant Mehta and Peter Grünwald
arXiv 1910.09227, 2019; Accepted to AISTATS 2020