Publications
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.
Titsias, M. et al. (2020) “FUNCTIONAL REGULARISATION FOR CONTINUAL LEARNING WITH GAUSSIAN PROCESSES”, in 8th International Conference on Learning Representations, ICLR 2020.
Jayakumar, S. et al. (2020) “MULTIPLICATIVE INTERACTIONS AND WHERE TO FIND THEM”, in 8th International Conference on Learning Representations, ICLR 2020.
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.
Xu, J. et al. (2020) “MetaFun: Meta-learning with iterative functional updates”, in 37th International Conference on Machine Learning, ICML 2020, pp. 10548–10558.
Sharma, M. et al. (2020) “How robust are the estimated effects of nonpharmaceutical interventions against COVID-19?”, in Advances in Neural Information Processing Systems.
Simsekli, U. et al. (2020) “Fractional underdamped langevin dynamics: Retargeting SGD with momentum under heavy-tailed gradient noise”, in 37th International Conference on Machine Learning, ICML 2020, pp. 8917–8927.
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.