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Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment.

international conference on machine learning, (2019)

Cited by: 20|Views115
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Abstract

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 efficient reinforcement learning approa...More

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Author
Walter Talbott
Walter Talbott
Miguel Ángel Bautista
Miguel Ángel Bautista
Shih-Yu Sun
Shih-Yu Sun
Josh Susskind
Josh Susskind
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