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Mayo, J. J., Hadiji, H., & van Erven, T. A. L. (2022). Scale-free Unconstrained Online Learning for Curved Losses. Proceedings of Machine Learning Research, 178. https://proceedings.mlr.press/v178/mayo22a.html
van der Hoeven, D., Hadiji, H., & van Erven, T. A. L. (2022). Distributed Online Learning for Joint Regret with Communication Constraints. Proceedings of Machine Learning Research, 167. https://proceedings.mlr.press/v167/hoeven22a.html
2021
van Erven, T., Koolen, W. M., & van der Hoeven, D. (2021). MetaGrad: Adaptation using Multiple Learning Rates in Online Learning. Journal of Machine Learning Research, 22(161), 1-61. https://jmlr.org/papers/v22/20-1444.html
van Erven, T., Sachs, S., Koolen, W. M., & Kotłowski, W. (2021). Robust Online Convex Optimization in the Presence of Outliers. Proceedings of Machine Learning Research, 134, 4174-4194. https://proceedings.mlr.press/v134/vanerven21a.html
2009
Koolen, W. M., & van Erven, T. (2009). Freezing and sleeping: Tracking experts that learn by evolving past posteriors. In M. van Erp, H. Stehouwer, & M. van Zaanen (Eds.), Benelearn 09: the 18th Annual Belgian-Dutch Conference on Machine Learning: proceedings of the conference (pp. 91-92). Tilburg centre for Creative Computing (TiCC), Tilburg University. http://benelearn09.uvt.nl/Proceedings_Benelearn_09.pdf[details]
2007
van Erven, T. A. L., Grünwald, P. D., & de Rooij, S. (2007). Catching Up Faster in Bayesian Model Selection and Model Averaging. In Advances in Neural Information Processing Systems (pp. 417-424). Neural Information Processing Systems (NIPS) Foundation. [details]
van Erven, T. A. L., de Rooij, S., & Grünwald, P. (2007). Switching between Predictors with an Application in Density Estimation. In Proceedings of the 28th Symposium on Information Theory in the Benelux (pp. 149-156). SAS. [details]
Others
van Erven, T. A. L. (other) (2007). Lecturer Machine Learning, Vrije Universiteit van Amsterdam (other).
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