Optimal rates of aggregation in classification under low noise assumption

Abstract

In the same spirit as Tsybakov, we define the optimality of an aggregation procedure in the problem of classification. Using an aggregate with exponential weights, we obtain an optimal rate of convex aggregation for the hinge risk under the margin assumption. Moreover, we obtain an optimal rate of model selection aggregation under the margin assumption for the excess Bayes risk.