On the inconsistency of separable losses for structured prediction

Caio Corro

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arXiv · 2301.10810

On the inconsistency of separable losses for structured prediction

Caio Corro

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Abstract

In this paper, we prove that separable negative log-likelihood losses for structured prediction are not necessarily Bayes consistent, or, in other words, minimizing these losses may not result in a model that predicts the most probable structure in the data distribution for a given input. This fact opens the question of whether these losses are well-adapted for structured prediction and, if so, why.

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Caio Corro. 2023-01-25. On the inconsistency of separable losses for structured prediction. https://arxiv.org/abs/2301.10810

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