  In this paper we present an enhancement of the regression-based variance
reduction approaches recently proposed in Belomestny et al. This enhancement is
based on a truncation of the control variate and allows for a significant
reduction of the computing time, while the complexity stays of the same order.
The performances of the proposed truncated algorithms are illustrated by a
numerical example.
