Learning-to-Learn Stochastic Gradient Descent with Biased Regularization

Giulia Denevi, Carlo Ciliberto, Riccardo Grazzi, Massimiliano Pontil

Abstract: We study the problem of learning-to-learn: infer- ring a learning algorithm that works well on a family of tasks sampled from an unknown distribution. As class of algorithms we consider Stochastic ...