Zobrazeno 1 - 10
of 85
pro vyhledávání: '"Andrés Montoyo"'
Autor:
Rosa Requena-Morales, Kristian Alonso-Stenberg, Blanca Patricia Silva-Barrera, Andrés Montoyo-Guijarro
Publikováno v:
RUA. Repositorio Institucional de la Universidad de Alicante
Universidad de Alicante (UA)
Universidad de Alicante (UA)
espanolLa prevalencia del consumo de sustancias se relaciona de forma bidireccional con los trastornos psiquiatricos severos causando impacto en los servicios de urgencias de los hospitales psiquiatricos. Objetivo. describir la prevalencia del consum
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b2c7d3cd05a78e3b65cb23932ef791dd
https://doi.org/10.21134/haaj.v21i1.548
https://doi.org/10.21134/haaj.v21i1.548
Autor:
Yoan Gutiérrez, Suilan Estevez-Velarde, Rafael Muñoz-Guillena, Andrés Montoyo, Alejandro Piad-Morffis, Yudivián Almeida Cruz, Hian Cañizares-Diaz
Publikováno v:
RANLP
This paper presents an active learning approach that aims to reduce the human effort required during the annotation of natural language corpora composed of entities and semantic relations. Our approach assists human annotators by intelligently select
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cc9d218abe7c8d926722dd2e9217c9e9
https://doi.org/10.26615/978-954-452-072-4_026
https://doi.org/10.26615/978-954-452-072-4_026
Autor:
Yudivián Almeida-Cruz, Rafael Muñoz, Alejandro Piad-Morffis, Yoan Gutiérrez, Ernesto Luis Estevanell-Valladares, Andrés Montoyo, Suilan Estevez-Velarde
Publikováno v:
NLP4COVID@EMNLP
RUA. Repositorio Institucional de la Universidad de Alicante
Universidad de Alicante (UA)
RANLP
RUA. Repositorio Institucional de la Universidad de Alicante
Universidad de Alicante (UA)
RANLP
This paper presents the preliminary results of an ongoing project that analyzes the growing body of scientific research published around the COVID-19 pandemic. In this research, a general-purpose semantic model is used to double annotate a batch of 5
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::511d3b73787fd64717edffe2a8dbf93f
https://hdl.handle.net/10045/110386
https://hdl.handle.net/10045/110386
Publikováno v:
RUA. Repositorio Institucional de la Universidad de Alicante
Universidad de Alicante (UA)
Universidad de Alicante (UA)
This paper introduces Hierarchical Machine Learning Optimisation (HML-Opt), an AutoML framework that is based on probabilistic grammatical evolution. HML-Opt has been designed to provide a flexible framework where a researcher can define the space of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ddea552270f3e2b8a5de3260c01f03d8
https://hdl.handle.net/10045/108428
https://hdl.handle.net/10045/108428
Publikováno v:
RUA. Repositorio Institucional de la Universidad de Alicante
Universidad de Alicante (UA)
COLING
Universidad de Alicante (UA)
COLING
This paper presents AutoGOAL, a system for automatic machine learning (AutoML) that uses heterogeneous techniques. In contrast with existing AutoML approaches, our contribution can automatically build machine learning pipelines that combine technique
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ea1defeee705135daf6569c8bf79c319
http://hdl.handle.net/10045/110740
http://hdl.handle.net/10045/110740
Autor:
Rafael Muñoz-Guillena, Andrés Montoyo, Alejandro Piad-Morffis, Yudivián Almeida Cruz, Yoan Gutiérrez, Suilan Estevez-Velarde
Publikováno v:
RUA. Repositorio Institucional de la Universidad de Alicante
Universidad de Alicante (UA)
COLING (Demonstrations)
Universidad de Alicante (UA)
COLING (Demonstrations)
This paper introduces a web demo that showcases the main characteristics of the AutoGOAL framework. AutoGOAL is a framework in Python for automatically finding the best way to solve a given task. It has been designed mainly for automatic machine lear
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8082100bae62c8cafcdcb68b4e85a022
http://hdl.handle.net/10045/110741
http://hdl.handle.net/10045/110741
Autor:
Yudivián Almeida-Cruz, Rafael Muñoz, Alejandro Piad-Morffis, Suilan Estevez-Velarde, Andrés Montoyo, Yoan Gutiérrez
Publikováno v:
RANLP
Scopus-Elsevier
Scopus-Elsevier
This paper presents Semantic Neural Networks (SNNs), a knowledge-aware component based on deep learning. SNNs can be trained to encode explicit semantic knowledge from an arbitrary knowledge base, and can subsequently be combined with other deep lear
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4389cd02be05706c4eed15f56e581e6f
https://doi.org/10.26615/978-954-452-056-4_105
https://doi.org/10.26615/978-954-452-056-4_105
Autor:
Suilan Estevez-Velarde, Yoan Gutiérrez, Andrés Montoyo, Alejandro Piad-Morffis, Rafael Muñoz, Yudivián Almeida-Cruz
Publikováno v:
RANLP
The massive amount of multi-formatted information available on the Web necessitates the design of software systems that leverage this information to obtain knowledge that is valid and useful. The main challenge is to discover relevant information and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::50d35356c1bfe782b889350c5451776d
https://doi.org/10.26615/978-954-452-056-4_032
https://doi.org/10.26615/978-954-452-056-4_032
Autor:
Yoan Gutiérrez, Andrés Montoyo, Miguel Lloret-Climent, Kristian Alonso, Rafael Muñoz Guillena
Purpose – The purpose of this paper is to propose a mathematical model to determine invariant sets, set covering, orbits and, in particular, attractors in the set of tourism variables. Analysis was carried out based on an algorithm and applying an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fbbf507117770d02334de7292eb5038b
https://hdl.handle.net/10045/88587
https://hdl.handle.net/10045/88587
Publikováno v:
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications ISBN: 9783030339036
CIARP
CIARP
This research presents NLP-Opt, an Auto-ML technique for optimizing pipelines of machine learning algorithms that can be applied to different Natural Language Processing tasks. The process of selecting the algorithms and their parameters is modelled
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aaa25b7cd43095b0bf54fb8eb4fb3cfb
https://doi.org/10.1007/978-3-030-33904-3_15
https://doi.org/10.1007/978-3-030-33904-3_15