Rianne de Heide

Rianne 

Probability and Statistics group
Department of Mathematics
NU building, room NU-9A13
Faculty of Science
Vrije Universiteit Amsterdam
De Boelelaan 1111, 1081 HV Amsterdam
E-mail: r.de.heide [at] vu [dot] nl

About me

I am an assistant professor in the Department of Mathematics, at the Vrije Universiteit Amsterdam. I work on problems and solutions in machine learning and statistics. My research focuses on sequential learning, and in particular on (sequential) hypothesis testing, Bayesian learning and best-arm identification problems. I am interested in exploring the limitations of existing methods under misspecification of the model or the data collecting process, and in devising new, robust methods for these settings. I’m also interested in the mathematical and philosophical foundations of Bayesianism, machine learning, statistics and probability theory.

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News

Research

My research interests include

  • Bandits, Reinforcement Learning

  • (Sequential) hypothesis testing

  • Group invariance in statistics

  • Bayesian methods

  • Learning theory

  • Foundations of ML, stats and probability theory

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Recent Publications

  • The truth-convergence of open-minded Bayesianism
    Tom F. Sterkenburg and Rianne de Heide
    The Review of Symbolic Logic 15(1):64-100, 2022, doi:10.1017/S1755020321000022    philsci archive   proc

  • Bandits with many optimal arms
    Rianne de Heide, James Cheshire, Pierre Ménard and Alexandra Carpentier
    NeurIPS 2021.    arxiv proc poster