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07/26/2023
General Purpose Artificial Intelligence Systems (GPAIS): Properties, Definition, Taxonomy, Open Challenges and Implications
Most applications of Artificial Intelligence (AI) are designed for a con...
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05/02/2023
Connecting the Dots in Trustworthy Artificial Intelligence: From AI Principles, Ethics, and Key Requirements to Responsible AI Systems and Regulation
Trustworthy Artificial Intelligence (AI) is based on seven technical req...
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02/20/2023
Multiobjective Evolutionary Pruning of Deep Neural Networks with Transfer Learning for improving their Performance and Robustness
Evolutionary Computation algorithms have been used to solve optimization...
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11/11/2022
REVEL Framework to measure Local Linear Explanations for black-box models: Deep Learning Image Classification case of study
Explainable artificial intelligence is proposed to provide explanations ...
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06/07/2022
TSFEDL: A Python Library for Time Series Spatio-Temporal Feature Extraction and Prediction using Deep Learning (with Appendices on Detailed Network Architectures and Experiment
The combination of convolutional and recurrent neural networks is a prom...
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05/20/2022
Exploring the Trade-off between Plausibility, Change Intensity and Adversarial Power in Counterfactual Explanations using Multi-objective Optimization
There is a broad consensus on the importance of deep learning models in ...
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04/21/2022
Handling Imbalanced Classification Problems With Support Vector Machines via Evolutionary Bilevel Optimization
Support vector machines (SVMs) are popular learning algorithms to deal w...
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02/08/2022
EvoPruneDeepTL: An Evolutionary Pruning Model for Transfer Learning based Deep Neural Networks
In recent years, Deep Learning models have shown a great performance in ...
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01/20/2022
Survey on Federated Learning Threats: concepts, taxonomy on attacks and defences, experimental study and challenges
Federated learning is a machine learning paradigm that emerges as a solu...
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01/17/2022
Data Harmonisation for Information Fusion in Digital Healthcare: A State-of-the-Art Systematic Review, Meta-Analysis and Future Research Directions
Removing the bias and variance of multicentre data has always been a cha...
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11/11/2021
Reducing Data Complexity using Autoencoders with Class-informed Loss Functions
Available data in machine learning applications is becoming increasingly...
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09/08/2021
A robust approach for deep neural networks in presence of label noise: relabelling and filtering instances during training
Deep learning has outperformed other machine learning algorithms in a va...
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05/26/2021
Anomaly Detection in Predictive Maintenance: A New Evaluation Framework for Temporal Unsupervised Anomaly Detection Algorithms
The research in anomaly detection lacks a unified definition of what rep...
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04/24/2021
EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: the MonuMAI cultural heritage use case
The latest Deep Learning (DL) models for detection and classification ha...
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04/23/2021
MULTICAST: MULTI Confirmation-level Alarm SysTem based on CNN and LSTM to mitigate false alarms for handgun detection in video-surveillance
Despite the constant advances in computer vision, integrating modern sin...
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10/08/2020
AT-MFCGA: An Adaptive Transfer-guided Multifactorial Cellular Genetic Algorithm for Evolutionary Multitasking
Transfer Optimization is an incipient research area dedicated to the sim...
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09/21/2020
CURIE: A Cellular Automaton for Concept Drift Detection
Data stream mining extracts information from large quantities of data fl...
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08/09/2020
Lights and Shadows in Evolutionary Deep Learning: Taxonomy, Critical Methodological Analysis, Cases of Study, Learned Lessons, Recommendations and Challenges
Much has been said about the fusion of bio-inspired optimization algorit...
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08/04/2020
Distributed Linguistic Representations in Decision Making: Taxonomy, Key Elements and Applications, and Challenges in Data Science and Explainable Artificial Intelligence
Distributed linguistic representations are powerful tools for modelling ...
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07/31/2020
Sentiment Analysis based Multi-person Multi-criteria Decision Making Methodology: Using Natural Language Processing and Deep Learning for Decision Aid
Decision making models are constrained by taking the expert evaluations ...
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07/29/2020
Dynamic Federated Learning Model for Identifying Adversarial Clients
Federated learning, as a distributed learning that conducts the training...
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07/15/2020
Revisiting Data Complexity Metrics Based on Morphology for Overlap and Imbalance: Snapshot, New Overlap Number of Balls Metrics and Singular Problems Prospect
Data Science and Machine Learning have become fundamental assets for com...
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07/02/2020
Federated Learning and Differential Privacy: Software tools analysis, the Sherpa.ai FL framework and methodological guidelines for preserving data privacy
The high demand of artificial intelligence services at the edges that al...
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05/21/2020
An analysis on the use of autoencoders for representation learning: fundamentals, learning task case studies, explainability and challenges
In many machine learning tasks, learning a good representation of the da...
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05/08/2020
A Showcase of the Use of Autoencoders in Feature Learning Applications
Autoencoders are techniques for data representation learning based on ar...
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04/19/2020
Fairness in Bio-inspired Optimization Research: A Prescription of Methodological Guidelines for Comparing Meta-heuristics
Bio-inspired optimization (including Evolutionary Computation and Swarm ...
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03/24/2020
Multifactorial Cellular Genetic Algorithm (MFCGA): Algorithmic Design, Performance Comparison and Genetic Transferability Analysis
Multitasking optimization is an incipient research area which is lately ...
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03/05/2020
Fuzzy k-Nearest Neighbors with monotonicity constraints: Moving towards the robustness of monotonic noise
This paper proposes a new model based on Fuzzy k-Nearest Neighbors for c...
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02/25/2020
Simultaneously Evolving Deep Reinforcement Learning Models using Multifactorial Optimization
In recent years, Multifactorial Optimization (MFO) has gained a notable ...
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02/19/2020
Comprehensive Taxonomies of Nature- and Bio-inspired Optimization: Inspiration versus Algorithmic Behavior, Critical Analysis and Recommendations
In recent years, a great variety of nature- and bio-inspired algorithms ...
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02/19/2020
Taxonomy of bio-inspired algorithms
In recent years, a great variety of nature and bio-inspired algorithms h...
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02/06/2020
LUNAR: Cellular Automata for Drifting Data Streams
With the advent of huges volumes of data produced in the form of fast st...
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01/16/2020
Smart Data based Ensemble for Imbalanced Big Data Classification
Big Data scenarios pose a new challenge to traditional data mining algor...
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10/22/2019
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI
In the last years, Artificial Intelligence (AI) has achieved a notable m...
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12/14/2018
A Tutorial on Distance Metric Learning: Mathematical Foundations, Algorithms and Software
This paper describes the discipline of distance metric learning, a branc...
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11/29/2018
A snapshot on nonstandard supervised learning problems: taxonomy, relationships and methods
Machine learning is a field which studies how machines can alter and ada...
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10/23/2018
OCAPIS: R package for Ordinal Classification And Preprocessing In Scala
Ordinal Data are those where a natural order exist between the labels. T...
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10/14/2018
DPASF: A Flink Library for Streaming Data preprocessing
Data preprocessing techniques are devoted to correct or alleviate errors...
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04/16/2018
BELIEF: A distance-based redundancy-proof feature selection method for Big Data
With the advent of Big Data era, data reduction methods are highly deman...
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03/27/2018
Towards Highly Accurate Coral Texture Images Classification Using Deep Convolutional Neural Networks and Data Augmentation
The recognition of coral species based on underwater texture images pose...
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02/14/2018
Dealing with Difficult Minority Labels in Imbalanced Mutilabel Data Sets
Multilabel classification is an emergent data mining task with a broad r...
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02/14/2018
Tackling Multilabel Imbalance through Label Decoupling and Data Resampling Hybridization
The learning from imbalanced data is a deeply studied problem in standar...
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02/10/2018
Tips, guidelines and tools for managing multi-label datasets: the mldr.datasets R package and the Cometa data repository
New proposals in the field of multi-label learning algorithms have been ...
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01/04/2018
A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines
Many of the existing machine learning algorithms, both supervised and un...
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06/03/2017
Deep-Learning Convolutional Neural Networks for scattered shrub detection with Google Earth Imagery
There is a growing demand for accurate high-resolution land cover maps i...
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03/21/2017
On the use of convolutional neural networks for robust classification of multiple fingerprint captures
Fingerprint classification is one of the most common approaches to accel...
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02/12/2017
Genetic and Memetic Algorithm with Diversity Equilibrium based on Greedy Diversification
The lack of diversity in a genetic algorithm's population may lead to a ...
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10/13/2016