Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment

15 May 2019Chen HuangShuangfei ZhaiWalter TalbottMiguel Angel BautistaShih-Yu SunCarlos GuestrinJosh Susskind

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... (read more)

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