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A Machine Learning Solution for Distributed Environments and Edge Computing
(MDPI AG, 2019-08-09)
[Abstract] In a society in which information is a cornerstone the exploding of data is crucial. Thinking of the Internet of Things, we need systems able to learn from massive data and, at the same time, being inexpensive ...
SOPRENE: Assessment of the Spanish Armada’s Predictive Maintenance Tool for Naval Assets
(MDPI, 2021)
[Abstract] Predictive maintenance has lately proved to be a useful tool for optimizing costs, performance and systems availability. Furthermore, the greater and more complex the system, the higher the benefit but also the ...
Feature Selection With Limited Bit Depth Mutual Information for Embedded Systems
(MDPI AG, 2018-09-17)
[Abstract] Data is growing at an unprecedented pace. With the variety, speed and volume of data flowing through networks and databases, newer approaches based on machine learning are required. But what is really big in Big ...
Improving Medical Data Annotation Including Humans in the Machine Learning Loop
(MDPI, 2021)
[Abstract] At present, the great majority of Artificial Intelligence (AI) systems require the participation of humans in their development, tuning, and maintenance. Particularly, Machine Learning (ML) systems could greatly ...
Machine Learning Techniques to Predict Different Levels of Hospital Care of CoVid-19
(Springer, 2022)
[Abstract] In this study, we analyze the capability of several state of the art machine learning methods to predict whether patients diagnosed with CoVid-19 (CoronaVirus disease 2019) will need different levels of hospital ...
A classification and review of tools for developing and interacting with machine learning systems
(Association for Computing Machinery, 2022)
[Abstract] In this paper we aim to bring some order to the myriad of tools that have emerged in the field of Artificial Intelligence (AI), focusing on the field of Machine Learning (ML). For this purpose, we suggest a ...
Integrating Iterative Machine Teaching and Active Learning into the Machine Learning Loop
(Elsevier, 2021)
[Abstract] Scholars and practitioners are defining new types of interactions between humans and machine learning algorithms that we can group under the umbrella term of Human-in-the-Loop Machine Learning (HITL-ML). This ...
Usability Heuristics for Domain-Specific Languages (DSLs)
(ACM, 2020-03-30)
[Abstract] The usability of Domain-Specific Languages (DSLs) has been attracting considerable interest from researchers lately. In particular, our literature review found many usability studies that make use of subjective ...
Quantum Computing for Dealing with Inaccurate Knowledge Related to the Certainty Factors Model
(MDPI, 2022)
[Abstract] In this paper, we illustrate that inaccurate knowledge can be efficiently implemented in a quantum environment. For this purpose, we analyse the correlation between certainty factors and quantum probability. We ...
A One-Class Classification method based on Expanded Non-Convex Hulls
(Elsevier, 2023)
[Abstract]: This paper presents an intuitive, robust and efficient One-Class Classification algorithm. The method developed is called OCENCH (One-class Classification via Expanded Non-Convex Hulls) and bases its operation ...