10 citations · 22 across the 11 of their papers we have counts for
4 papers · 1 filter
Federated Learning with Nonvacuous Generalisation Bounds
Pierre Jobic, Maxime Haddouche, Benjamin Guedj
We introduce a novel strategy to train randomised predictors in federated learning, where each node of the network aims at preserving its privacy by releasing a local predictor but…
Online (Non-)Convex Learning via Tempered Optimism
Maxime Haddouche, Olivier Wintenberger, Benjamin Guedj
Optimistic Online Learning aims to exploit experts conveying reliable information to predict the future. However, such implicit optimism may be challenged when it comes to practica…
Online PAC-Bayes Learning
Maxime Haddouche, Benjamin Guedj
Most PAC-Bayesian bounds hold in the batch learning setting where data is collected at once, prior to inference or prediction. This somewhat departs from many contemporary learning…
Upper and Lower Bounds on the Performance of Kernel PCA
Maxime Haddouche, Benjamin Guedj, John Shawe-Taylor
Principal Component Analysis (PCA) is a popular method for dimension reduction and has attracted an unfailing interest for decades. More recently, kernel PCA (KPCA) has emerged as…