We present a novel Bayesian approach to the problem of value function estimation in continuous state spaces. We define a probabilistic generative model for the value function by i...
We investigate the use of certain data-dependent estimates of the complexity of a function class, called Rademacher and Gaussian complexities. In a decision theoretic setting, we ...
The design process for an engine management system is presented. The functional specification of the system has been captured using C and C++ as specification languages. The val...
Massimo Baleani, Alberto Ferrari, Alberto L. Sangi...
This paper provides a new framework for the derivation and estimation of consumption and the equity premium functions. The novelty in our approach is that it does not require the ...
We evaluate probability density functions of diffusivity measures in DTI fiber tracts as biomarkers. For this, we estimate univariate and bivariate densities, such as joint probabi...