85 citations · 100 across the 5 of their papers we have counts for
3 papers · 1 filter
Risk Bounds for the Majority Vote: From a PAC-Bayesian Analysis to a Learning Algorithm
Pascal Germain, Alexandre Lacasse, François Laviolette +2
We propose an extensive analysis of the behavior of majority votes in binary classification. In particular, we introduce a risk bound for majority votes, called the C-bound, that t…
On Generalizing the C-Bound to the Multiclass and Multi-label Settings
Francois Laviolette, Emilie Morvant, Liva Ralaivola +1
The C-bound, introduced in Lacasse et al., gives a tight upper bound on the risk of a binary majority vote classifier. In this work, we present a first step towards extending this…
On the Generalization of the C-Bound to Structured Output Ensemble Methods
François Laviolette, Emilie Morvant, Liva Ralaivola +1
This paper generalizes an important result from the PAC-Bayesian literature for binary classification to the case of ensemble methods for structured outputs. We prove a generic ver…