Set Learning for Accurate and Calibrated Models

Lukas Muttenthaler, Robert A. Vandermeulen, Qiuyi Zhang +2

Model overconfidence and poor calibration are common in machine learning and difficult to account for when applying standard empirical risk minimization. In this work, we propose a…