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Mostrando ítems 1-10 de 10
Artículo
Autoencoded DNA methylation data to predict breast cancer recurrence: Machine learning models and gene-weight significance
(Elsevier, 2020)
Breast cancer is the most frequent cancer in women and the second most frequent overall after lung cancer. Although the 5-year survival rate of breast cancer is relatively high, recurrence is also common which often ...
Artículo
Statistically Representative Metrology of Nanoparticles via Unsupervised Machine Learning of TEM Images
(MDPI, 2021)
The morphology of nanoparticles governs their properties for a range of important applica tions. Thus, the ability to statistically correlate this key particle performance parameter is paramount in achieving accurate ...
Ponencia
Towards the smart use of embedding and instance features for property matching
(IEEE Computer Society, 2021)
Data integration tasks such as the creation and extension of knowledge graphs involve the fusion of heterogeneous entities from many sources. Matching and fusion of such entities require to also match and combine their ...
Ponencia
Performance of Algorithms for Interval Discretization of Biomedical Signals
(Springer, 2016)
A methodology to quantify the dependence be tween features using the Ameva discretization algorithm and the advantages of qualitative models is presented in this paper. This approach will be applied over medical data ...
Ponencia
Towards a unified model representation of machine learning knowledge
(SciTePress, 2019)
Nowadays, Machine Learning (ML) algorithms are being widely applied in virtually all possible scenarios. However, developing a ML project entails the effort of many ML experts who have to select and configure the appropriate ...
Ponencia
Un Recorrido por los Principales Proveedores de Servicios de Machine Learning y Predicción en la Nube
(Sociedad de Ingeniería de Software y Tecnologías de Desarrollo de Software (SISTEDES), 2018)
Los medios tecnológicos para el consumo, producción e intercambio de información no hacen más que aumentar cada día que pasa. Nos encontramos envueltos en el fenómeno Big Data, donde ser capaces de analizar esta informa ...
Artículo
LEAPME: learning-based property matching with embeddings
(Elsevier, 2022)
Data integration tasks such as the creation and extension of knowledge graphs involve the fusion of heterogeneous entities from many sources. Matching and fusion of such entities require to also match and combine their ...
Artículo
CAFE: Knowledge graph completion using neighborhood-aware features
(Elsevier, 2021)
Knowledge Graphs (KGs) currently contain a vast amount of structured information in the form of entities and relations. Because KGs are often constructed automatically by means of information extraction processes, they ...
Ponencia
VaryLATEX: Learning Paper Variants That Meet Constraints
(ACM: Association for Computing Machinery, 2018)
How to submit a research paper, a technical report, a grant pro posal, or a curriculum vitae that respect imposed constraints such as formatting instructions and page limits? It is a challenging task, especially when ...
Artículo
CAFE: Fact Checking in Knowledge Graphs using Neighborhood-Aware Features
(IOS Press, 2020)
Knowledge Graphs (KGs) currently contain a vast amount of structured information in the form of entities and relations. Because KGs are often constructed automatically by means of information extraction processes, they ...