Upper and Lower Tight Error Bounds for Feature Omission with an Extension to Context Reduction

Autor:	Eugen Beck, Ralf Schlüter, Hermann Ney
Jazyk:	angličtina
Rok vydání:	2019
Předmět:	Context model Computer science business.industry Applied Mathematics Feature extraction String (computer science) Context (language use) Feature selection 02 engineering and technology Upper and lower bounds Reduction (complexity) Computational Theory and Mathematics Artificial Intelligence 0202 electrical engineering electronic engineering information engineering Feature (machine learning) 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Language model Artificial intelligence business Algorithm Software
Zdroj:	IEEE transactions on pattern analysis and machine intelligence : TPAMI 41(2), 502-514 (2019). doi:10.1109/TPAMI.2017.2788434 IEEE Transactions on Pattern Analysis and Machine Intelligence
DOI:	10.1109/TPAMI.2017.2788434
Popis:	IEEE transactions on pattern analysis and machine intelligence : TPAMI 41(2), 502-514 (2019). doi:10.1109/TPAMI.2017.2788434 Published by IEEE, New York, NY
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f3ad2d758a1651a92aa15d1215287377 https://publications.rwth-aachen.de/record/755689 Zobrazit plný text záznamu