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It is the goal of this paper to extend the \textit{Empirical Risk Minimization} (ERM) paradigm, from a practical perspective, to the situation where a natural estimate of the risk is of the form of a $K$-sample $U$-stati...
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One main focus of learning theory is to find optimal rates of convergence. In classification, it is possible to obtain optimal fast rates (faster than nā1/2) in a minimax sense. Moreover, using an aggregation procedure, ...
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While it is now well-known in the standard binary classi cation setup, that, under suitable margin assumptions and complexity conditions on the regression function, fast or even super-fast rates can be achieved by plug-i...