Online Parameter-Free Learning of Multiple Low Variance Tasks

Giulia Denevi, Massimiliano Pontil, Dimitrios Stamos

Abstract: We propose a method to learn a common bias vector for a growing sequence of low-variance tasks. Unlike state-of-the-art approaches, our method does not require tuning any hyper-parameter. Our appro...