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Publications

Gaunt, R. and Reinert, G. (2021) “Bounds for the chi-square approximation of Friedman’s statistic by Stein’s method.”
Oravkin, E. and Rebeschini, P. (2021) “On Optimal Interpolation In Linear Regression”, arXiv.
He, Y. et al. (2021) “SSSNET: Semi-Supervised Signed Network Clustering.”
Di Benedetto, G., Caron, F. and Teh, Y. (2021) “Non-exchangeable random partition models for microclustering”, Annals of Statistics, 49(4), pp. 1931–1957.
Di Benedetto, G., Caron, F. and Teh, Y. (2021) “Non-exchangeable random partition models for microclustering”, Annals of Statistics, 49(4), pp. 1931–1957.
Nicholson, G. et al. (2021) “Interoperability of statistical models in pandemic preparedness: principles and reality”, arXiv.
Alfano, C. and Rebeschini, P. (2021) “Dimension-Free Rates for Natural Policy Gradient in Multi-Agent Reinforcement Learning”, arXiv.
Barbour, A. and Reinert, G. (2021) “Estimating the correlation in network disturbance models”, Journal of Complex Networks, 9(5).
Wu, F. and Rebeschini, P. (2021) “Hadamard wirtinger flow for sparse phase retrieval”, in Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS 2021). Journal of Machine Learning Research, pp. 982–990.
Richards, D., Dobriban, E. and Rebeschini, P. (2021) “Comparing Classes of Estimators: When does Gradient Descent Beat Ridge Regression in Linear Models?”, arXiv.