Estimating an overall density function from repeated observations on each of a sample of independent subjects or experimental units is of interest. An example is provided by biodem...
We introduce an algorithm that learns gradients from samples in the supervised learning framework. An error analysis is given for the convergence of the gradient estimated by the ...
We introduce an algorithm that simultaneously estimates a classification function as well as its gradient in the supervised learning framework. The motivation for the algorithm is...
Summary: BATS is a user-friendly software for Bayesian Analysis of Time Series microarray experiments based on the novel, truly functional and fully Bayesian approach proposed in ...
Claudia Angelini, Luisa Cutillo, Daniela De Candit...
We propose a new penalty function which, when used as regularization for empirical risk minimization procedures, leads to sparse estimators. The support of the sparse vector is ty...