The regularization parameter choice is a fundamental problem in supervised learning since the performance of most algorithms crucially depends on the choice of one or more of such parameters. In particular a main theoretical ...

A common objective in learning a model from data is to recover its network structure, while the model parameters are of minor interest. For example, we may wish to recover regulatory networks from high-throughput data ...