Publications

Di Benedetto, G., Caron, F. and Teh, Y. (2020) “Non-exchangeable feature allocation models with sublinear growth of the feature sizes”, arXiv.

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.

Bhutta, M. et al. (2019) “Transcript Analysis Reveals a Hypoxic Inflammatory Environment in Human Chronic Otitis Media With Effusion”, Frontiers in Genetics, 10, p. 1327.

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.

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.

He, B., Lakshminarayanan, B. and Teh, Y. (2020) “Bayesian deep ensembles via the neural tangent kernel”, in Advances in Neural Information Processing Systems.

Zhou, Y. et al. (2020) “Divide, conquer, and combine: A new inference strategy for Probabilistic Programs with Stochastic Support”, 37th International Conference on Machine Learning, ICML 2020, PartF168147-15, pp. 11471–11482.

Camuto, A. et al. (2020) “Explicit regularisation in Gaussian noise injections”, in Advances in Neural Information Processing Systems.