Rianne de Heide
- Full Name
- Dr. R. de Heide
- Function(s)
- Researcher - Vrije Universiteit
- R.de.Heide@cwi.nl
- Telephone
- +31 20 592 4244
- Room
- L136
- Department(s)
- Machine Learning
- Homepage
- https://homepages.cwi.nl/~heide/
Publications
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de Heide, R, Cheshire, J, Ménard, P, & Carpentier, A. (2021). Bandits with many optimal arms. In Proceedings NeurIPS (Annual Conference on Neural Information Processing Systems).
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Hendriksen, A.A, de Heide, R, & Grünwald, P.D. (2021). Optional stopping with Bayes factors: A categorization and extension of folklore results, with an application to invariant situations. Bayesian Analysis, 16(3), 961–989. doi:10.1214/20-BA1234
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Sterkenburg, T.F, & de Heide, R. (2021). On the truth-convergence of open-minded Bayesianism. The Review of Symbolic Logic, 1–37. doi:http://dx.doi:10.1017/S1755020321000022
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de Heide, R. (2021, January 26). Bayesian Learning: Challenges, Limitations and Pragmatics.
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Smit, P.-B, & de Heide, R. (2021). God, the beautiful and mathematics: A response. HTS Teologiese Studies / Theological Studies, 77(4). doi:10.4102/hts.v77i4.6208
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de Heide, R, Kirichenko, A.A, Mehta, N.A, & Grünwald, P.D. (2020). Safe-Bayesian Generalized Linear Regression. In Proceedings of the International Conference on Artificial Intelligence and Statistics (pp. 2623–2633).
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Shang, X, de Heide, R, Kaufmann, E, Ménard, P, & Valko, M. (2020). Fixed-confidence guarantees for Bayesian best-arm identification. In Proceedings of the International Conference on Artificial Intelligence and Statistics (pp. 1823–1832).
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Grünwald, P.D, & de Heide, R. (2018). Invited discussion to the paper Using Stacking to Average Bayesian Predictive Distributions by Yao, Vehtari, Simpson and Gelman. Bayesian Analysis, 13(3), 917–1003.