Имитационное обучение

method ID: imitationlearning

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Feature computation and exhaustive search have significantly restricted the speed of graph-based dependency parsing. We propose a faster framework of dynamic feature selec- tion, where features are added sequentially as …...

34622

Extracting Relations between Non-Standard Entities using Distant Supervision and Imitation Learning

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Distantly supervised approaches have be- come popular in recent years as they allow training relation extractors without text- bound annotation, using instead known relations from a knowledge base and a …...

34726

Imitation Learning of Agenda-based Semantic Parsers

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AbstractSemantic parsers conventionally construct logical forms bottom-up in a fixed order, resulting in the generation of many extraneous partial logical forms. In this paper, we combine ideas from imitation learning …...

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AbstractNatural language generation (NLG) is the task of generating natural language from a meaning representation. Current rule-based approaches require domain-specific and manually constructed linguistic resources, while most machine-learning based approaches …...

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Meaning Representation parsing James Goodman∗ Andreas Vlachos† Jason Naradowsky∗ ∗ Computer Science Department, University College London james@janigo.co.uk, jason.narad@gmail.com † Department of Computer Science, University of Sheffield a.vlachos@sheffield.ac.uk Abstract Semantic parsers …...

40638

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42583