85 citations · 100 across the 5 of their papers we have counts for
3 papers · 1 filter
Efficient Learning of Ensembles with QuadBoost
Louis Fortier-Dubois, François Laviolette, Mario Marchand +2
We first present a general risk bound for ensembles that depends on the Lp norm of the weighted combination of voters which can be selected from a continuous set. We then propose a…
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…