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Joint Structured Learning and Predictions under Logical Constraints in Conditional Random Fields

2017/08/25 by Jean-Luc Meunier, Meunier, Jean-Luc, Jean‐Luc Meunier
Computer Science · Mathematics · #Machine Learning and Data Classification #cs.LG #stat.ML

paper · pdf · doi:10.48550/arxiv.1708.07644

CAp 2017 (Conférence sur l'Apprentissage automatique)

arxiv created 2017/08/25 · arxiv updated 2017/08/28

Abstract

This paper is concerned with structured machine learning, in a supervised machine learning context. It discusses how to make joint structured learning on interdependent objects of different nature, as well as how to enforce logical con-straints when predicting labels. We explain how this need arose in a Document Understanding task. We then discuss a general extension to Conditional Random Field (CRF) for this purpose and present the contributed open source implementation on top of the open source PyStruct library. We evaluate its performance on a publicly available dataset.

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