86 citations · 112 across the 10 of their papers we have counts for
10 papers
Semantic-Inductive Attribute Selection for Zero-Shot Learning
Juan Jose Herrera-Aranda, Guillermo Gomez-Trenado, Francisco Herrera +1
Zero-Shot Learning is an important paradigm within General-Purpose Artificial Intelligence Systems, particularly in those that operate in open-world scenarios where systems must ad…
Evolutionary Computation for the Design and Enrichment of General-Purpose Artificial Intelligence Systems: Survey and Prospects
Javier Poyatos, Javier Del Ser, Salvador Garcia +6
In Artificial Intelligence, there is an increasing demand for adaptive models capable of dealing with a diverse spectrum of learning tasks, surpassing the limitations of systems de…
The Energy Prediction Smart-Meter Dataset: Analysis of Previous Competitions and Beyond
Direnc Pekaslan, Jose Maria Alonso-Moral, Kasun Bandara +17
This paper presents the real-world smart-meter dataset and offers an analysis of solutions derived from the Energy Prediction Technical Challenges, focusing primarily on two key co…
General Purpose Artificial Intelligence Systems (GPAIS): Properties, Definition, Taxonomy, Societal Implications and Responsible Governance
Isaac Triguero, Daniel Molina, Javier Poyatos +2
Most applications of Artificial Intelligence (AI) are designed for a confined and specific task. However, there are many scenarios that call for a more general AI, capable of solvi…
AutoEn: An AutoML method based on ensembles of predefined Machine Learning pipelines for supervised Traffic Forecasting
Juan S. Angarita-Zapata, Antonio D. Masegosa, Isaac Triguero
Intelligent Transportation Systems are producing tons of hardly manageable traffic data, which motivates the use of Machine Learning (ML) for data-driven applications, such as Traf…
Local-Global Methods for Generalised Solar Irradiance Forecasting
Timothy Cargan, Dario Landa-Silva, Isaac Triguero
As the use of solar power increases, having accurate and timely forecasts will be essential for smooth grid operators. There are many proposed methods for forecasting solar irradia…
CzSL: Learning from citizen science, experts and unlabelled data in astronomical image classification
Manuel Jimenez, Emilio J. Alfaro, Mercedes Torres Torres +1
Citizen science is gaining popularity as a valuable tool for labelling large collections of astronomical images by the general public. This is often achieved at the cost of poorer…
Predict+Optimize Problem in Renewable Energy Scheduling
Christoph Bergmeir, Frits de Nijs, Evgenii Genov +25
Predict+Optimize frameworks integrate forecasting and optimization to address real-world challenges such as renewable energy scheduling, where variability and uncertainty are criti…
L2AE-D: Learning to Aggregate Embeddings for Few-shot Learning with Meta-level Dropout
Heda Song, Mercedes Torres Torres, Ender Özcan +1
Few-shot learning focuses on learning a new visual concept with very limited labelled examples. A successful approach to tackle this problem is to compare the similarity between ex…
On the use of convolutional neural networks for robust classification of multiple fingerprint captures
Daniel Peralta, Isaac Triguero, Salvador García +3
Fingerprint classification is one of the most common approaches to accelerate the identification in large databases of fingerprints. Fingerprints are grouped into disjoint classes,…