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A computational system for the Heuristic Forecasting of Fire Risk
(International Institute of Informatics and Systemics, 2002-07)
This article describes a computational system which forecasts the potential risk of forest fires, by processing a set of
meteorological variables so as to produce a fire weather risk index. The system also studies a set ...
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 ...
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 ...
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 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 ...