research
∙
06/07/2023
Learning via Wasserstein-Based High Probability Generalisation Bounds
Minimising upper bounds on the population risk or the generalisation gap...
share
research
∙
04/14/2023
Wasserstein PAC-Bayes Learning: A Bridge Between Generalisation and Optimisation
PAC-Bayes learning is an established framework to assess the generalisat...
research
∙
01/18/2023
Optimistic Dynamic Regret Bounds
Online Learning (OL) algorithms have originally been developed to guaran...
research
∙
10/03/2022
PAC-Bayes with Unbounded Losses through Supermartingales
While PAC-Bayes is now an established learning framework for bounded los...
research
∙
05/31/2022
Online PAC-Bayes Learning
Most PAC-Bayesian bounds hold in the batch learning setting where data i...
research
∙
12/18/2020
Upper and Lower Bounds on the Performance of Kernel PCA
Principal Component Analysis (PCA) is a popular method for dimension red...
research
∙
06/12/2020
