Laboratorio de Investigación e Desenvolvemento en Intelixencia Artificial (LIDIA): Envíos recentes
Mostrando ítems 36-40 de 90
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Quantum Factory Method: A Software Engineering Approach to Deal with Incompatibilities in Quantum Libraries
(Springer Nature, 2023-06)[Abstract]: The current context of Quantum Computing and its available technologies present an extensive variety of tools and lack of methodologies, leading to incompatibilities across platforms, which end up as inconsistencies ... -
A Convolutional Network for Sleep Stages Classification
(2019-02)[Abstract]: Sleep stages classification is a crucial task in the context of sleep studies. It involves the simultaneous analysis of multiple signals recorded during sleep. However, it is complex and tedious, and even the ... -
Addressing the data bottleneck in medical deep learning models using a human-in-the-loop machine learning approach
(Springer Nature, 2023-11)[Abstract]: Any machine learning (ML) model is highly dependent on the data it uses for learning, and this is even more important in the case of deep learning models. The problem is a data bottleneck, i.e. the difficulty ... -
On the Reliability of Machine Learning Models for Survival Analysis When Cure Is a Possibility
(MDPI, 2023-10-02)[Abstract]: In classical survival analysis, it is assumed that all the individuals will experience the event of interest. However, if there is a proportion of subjects who will never experience the event, then a standard ... -
On developing an automatic threshold applied to feature selection ensembles
(Elsevier, 2019-01)[Abstract]: Feature selection ensemble methods are a recent approach aiming at adding diversity in sets of selected features, improving performance and obtaining more robust and stable results. However, using an ensemble ...
