Výsledky vyhledávání - "Ferro, Jesus A"

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Absolute convergence and error thresholds in non-active adaptive sampling

Autor: Ferro, Manuel Vilares, Bilbao, Victor M. Darriba, Ferro, Jesús Vilares

Publikováno v: Journal of Computer and System Sciences, 129 (2020) , pp 39-61. ISSN 1090-2724. Elsevier

Non-active adaptive sampling is a way of building machine learning models from a training data base which are supposed to dynamically and automatically derive guaranteed sample size. In this context and regardless of the strategy used in both schedul

Externí odkaz: http://arxiv.org/abs/2402.02522

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Adaptive scheduling for adaptive sampling in POS taggers construction

Autor: Ferro, Manuel Vilares, Bilbao, Victor M. Darriba, Ferro, Jesús Vilares

Publikováno v: Computer Speech & Language, 60, 101020 (2020), pp 1-18. ISSN 0885-2308. Elsevier

We introduce an adaptive scheduling for adaptive sampling as a novel way of machine learning in the construction of part-of-speech taggers. The goal is to speed up the training on large data sets, without significant loss of performance with regard t

Externí odkaz: http://arxiv.org/abs/2402.02516

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Akademický článek

Differences in global gene expression in muscle tissue of Nellore cattle with divergent meat tenderness

Autor: Fonseca, Larissa Fernanda Simielli, Gimenez, Daniele Fernanda Jovino, dos Santos Silva, Danielly Beraldo, Barthelson, Roger, Baldi, Fernando, Ferro, Jesus Aparecido, Albuquerque, Lucia Galvão

Background: Meat tenderness is the consumer's most preferred sensory attribute. This trait is affected by a number of factors, including genotype, age, animal sex, and pre-and post-slaughter management. In view of the high percentage of Zebu genes in

Externí odkaz: http://hdl.handle.net/10150/626423
http://arizona.openrepository.com/arizona/handle/10150/626423

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