2019
Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment
ICML 2019oral
In most machine learning training paradigms a fixed, often handcrafted, loss function is assumed to be a good proxy for an underlying evaluation metric. In this work we assess this assumption by meta-learning an adaptive loss function to directly optimize the evaluation metric. We propose a sample e…