University of Oxford, Department of Statistics logo
University of Oxford, Department of Statistics logo
To Department of Statistics Site

Publications

Todeschini, A., Miscouridou, X. and Caron, F. (2020) “Exchangeable random measures for sparse and modular graphs with overlapping communities”, Journal of the Royal Statistical Society Series B: Statistical Methodology, 82(2), pp. 487–520.
Vaškevičius, T., Kanade, V. and Rebeschini, P. (2020) “The Statistical Complexity of Early-Stopped Mirror Descent”, arXiv.
Fong, E. and Holmes, C. (2020) “On the marginal likelihood and crossvalidation”, Biometrika, 107(2), pp. 489–496.
Richards, D. and Rebeschini, P. (2020) “Graph-dependent implicit regularisation for distributed stochastic subgradient descent”, Journal of Machine Learning Research, 21(2020), pp. 1–44.
Lee, J. et al. (2020) “Bootstrapping neural processes”, in Advances in Neural Information Processing Systems.
He, B., Lakshminarayanan, B. and Teh, Y. (2020) “Bayesian deep ensembles via the neural tangent kernel”, in Advances in Neural Information Processing Systems.
Sharma, M. et al. (2020) “How robust are the estimated effects of nonpharmaceutical interventions against COVID-19?”, in Advances in Neural Information Processing Systems.
Richards, D., Rebeschini, P. and Rosasco, L. (2020) “Decentralised learning with distributed gradient descent and random features”, in 37th International Conference on Machine Learning Icml 2020, pp. 8075–8085.
Jayakumar, S. et al. (2020) “MULTIPLICATIVE INTERACTIONS AND WHERE TO FIND THEM”, in 8th International Conference on Learning Representations, ICLR 2020.
Xu, J. et al. (2020) “MetaFun: Meta-learning with iterative functional updates”, in 37th International Conference on Machine Learning, ICML 2020, pp. 10548–10558.