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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 ... -
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 ... -
Case Study of Anomaly Detection and Quality Control of Energy Efficiency and Hygrothermal Comfort in Buildings
(2019)[Abstract] The aim of this work is to propose different statistical and machine learning methodologies for identifying anomalies and control the quality of energy efficiency and hygrothermal comfort in buildings. ... -
On the Effectiveness of Convolutional Autoencoders on Image-Based Personalized Recommender Systems
(MDPI AG, 2020-08-19)[Abstract] Over the years, the success of recommender systems has become remarkable. Due to the massive arrival of options that a consumer can have at his/her reach, a collaborative environment was generated, where users ... -
An Intelligent and Collaborative Multiagent System in a 3D Environment
(MDPI AG, 2020-08-21)[Abstract] Multiagent systems (MASs) allow facing complex, heterogeneous, distributed problems difficult to solve by only one software agent. The world of video games provides problems and suitable environments for the use ...