49 citations · 412 across the 50 of their papers we have counts for
4 papers · 2 filters
Simpler PAC-Bayesian Bounds for Hostile Data
Pierre Alquier, Benjamin Guedj
PAC-Bayesian learning bounds are of the utmost interest to the learning community. Their role is to connect the generalization ability of an aggregation distribution to its emp…
Stability revisited: new generalisation bounds for the Leave-one-Out
Alain Celisse, Benjamin Guedj
The present paper provides a new generic strategy leading to non-asymptotic theoretical guarantees on the Leave-one-Out procedure applied to a broad class of learning algorithms. T…
A Quasi-Bayesian Perspective to Online Clustering
Le Li, Benjamin Guedj, Sébastien Loustau
When faced with high frequency streams of data, clustering raises theoretical and algorithmic pitfalls. We introduce a new and adaptive online clustering algorithm relying on a qua…
An Oracle Inequality for Quasi-Bayesian Non-Negative Matrix Factorization
Pierre Alquier, Benjamin Guedj
The aim of this paper is to provide some theoretical understanding of quasi-Bayesian aggregation methods non-negative matrix factorization. We derive an oracle inequality for an ag…