On the inconsistency of separable losses for structured prediction
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3ASE32PDW8" target="_blank" >RIV/00216208:11320/23:SE32PDW8 - isvavai.cz</a>
Result on the web
<a href="http://arxiv.org/abs/2301.10810" target="_blank" >http://arxiv.org/abs/2301.10810</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
On the inconsistency of separable losses for structured prediction
Original language description
"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."
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů