On the inconsistency of separable losses for structured prediction

Caio Corro
1/25/2023
cs.LGcs.CLstat.ML

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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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Cite this paper

@article{corro2023inconsistency,
  title  = {On the inconsistency of separable losses for structured prediction},
  author = {Caio Corro},
  year   = {2023},
  eprint = {2301.10810},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2301.10810v1}
}

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