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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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05/24/2023
ChatAgri: Exploring Potentials of ChatGPT on Cross-linguistic Agricultural Text Classification
In the era of sustainable smart agriculture, a massive amount of agricul...
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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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04/18/2023
Using Offline Data to Speed-up Reinforcement Learning in Procedurally Generated Environments
One of the key challenges of Reinforcement Learning (RL) is the ability ...
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03/14/2023
On the Connection between Concept Drift and Uncertainty in Industrial Artificial Intelligence
AI-based digital twins are at the leading edge of the Industry 4.0 revol...
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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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12/07/2022
Deep Learning for Brain Age Estimation: A Systematic Review
Over the years, Machine Learning models have been successfully employed ...
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11/30/2022
Towards Improving Exploration in Self-Imitation Learning using Intrinsic Motivation
Reinforcement Learning has emerged as a strong alternative to solve opti...
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10/28/2022
Measuring the Confidence of Traffic Forecasting Models: Techniques, Experimental Comparison and Guidelines towards Their Actionability
The estimation of the amount of uncertainty featured by predictive machi...
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09/30/2022
A Novel Explainable Out-of-Distribution Detection Approach for Spiking Neural Networks
Research around Spiking Neural Networks has ignited during the last year...
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09/29/2022
Accurate Long-term Air Temperature Prediction with a Fusion of Artificial Intelligence and Data Reduction Techniques
In this paper three customised Artificial Intelligence (AI) frameworks, ...
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09/26/2022
Greybox XAI: a Neural-Symbolic learning framework to produce interpretable predictions for image classification
Although Deep Neural Networks (DNNs) have great generalization and predi...
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09/17/2022
Non-Imaging Medical Data Synthesis for Trustworthy AI: A Comprehensive Survey
Data quality is the key factor for the development of trustworthy AI in ...
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08/11/2022
Region-Based Evidential Deep Learning to Quantify Uncertainty and Improve Robustness of Brain Tumor Segmentation
Despite recent advances in the accuracy of brain tumor segmentation, the...
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07/28/2022
Deep learning for understanding multilabel imbalanced Chest X-ray datasets
Over the last few years, convolutional neural networks (CNNs) have domin...
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07/19/2022
Large-Kernel Attention for 3D Medical Image Segmentation
Automatic segmentation of multiple organs and tumors from 3D medical ima...
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07/18/2022
Capabilities, Limitations and Challenges of Style Transfer with CycleGANs: A Study on Automatic Ring Design Generation
Rendering programs have changed the design process completely as they pe...
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06/03/2022
Analysis, Characterization, Prediction and Attribution of Extreme Atmospheric Events with Machine Learning: a Review
Atmospheric Extreme Events (EEs) cause severe damages to human societies...
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05/23/2022
An Evaluation Study of Intrinsic Motivation Techniques applied to Reinforcement Learning over Hard Exploration Environments
In the last few years, the research activity around reinforcement learni...
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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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02/24/2022
Collaborative Training of Heterogeneous Reinforcement Learning Agents in Environments with Sparse Rewards: What and When to Share?
In the early stages of human life, babies develop their skills by explor...
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02/11/2022
Explainable COVID-19 Infections Identification and Delineation Using Calibrated Pseudo Labels
The upheaval brought by the arrival of the COVID-19 pandemic has continu...
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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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01/31/2022
AI-based Medical e-Diagnosis for Fast and Automatic Ventricular Volume Measurement in the Patients with Normal Pressure Hydrocephalus
Based on CT and MRI images acquired from normal pressure hydrocephalus (...
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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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01/11/2022
On the Design of Graph Embeddings for the Sensorless Estimation of Road Traffic Profiles
Traffic forecasting models rely on data that needs to be sensed, process...
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12/10/2021
Edge-Enhanced Dual Discriminator Generative Adversarial Network for Fast MRI with Parallel Imaging Using Multi-view Information
In clinical medicine, magnetic resonance imaging (MRI) is one of the mos...
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11/29/2021
Evolutionary Multitask Optimization: Are we Moving in the Right Direction?
Transfer Optimization, understood as the exchange of information among s...
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04/02/2021
Explainable Artificial Intelligence (XAI) on TimeSeries Data: A Survey
Most of state of the art methods applied on time series consist of deep ...
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03/28/2021
A survey on extremism analysis using Natural Language Processing
Extremism research has grown as an open problem for several countries du...
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03/26/2021
Randomization-based Machine Learning in Renewable Energy Prediction Problems: Critical Literature Review, New Results and Perspectives
Randomization-based Machine Learning methods for prediction are currentl...
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02/17/2021
On the Post-hoc Explainability of Deep Echo State Networks for Time Series Forecasting, Image and Video Classification
Since their inception, learning techniques under the Reservoir Computing...
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02/04/2021
Evolutionary Multitask Optimization: a Methodological Overview, Challenges and Future Research Directions
In this work we consider multitasking in the context of solving multiple...
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12/02/2020
Deep Learning for Road Traffic Forecasting: Does it Make a Difference?
Deep Learning methods have been proven to be flexible to model complex p...
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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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09/30/2020
A Coevolutionary Variable Neighborhood Search Algorithm for Discrete Multitasking (CoVNS): Application to Community Detection over Graphs
The main goal of the multitasking optimization paradigm is to solve mult...
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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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05/11/2020
On the Transferability of Knowledge among Vehicle Routing Problems by using Cellular Evolutionary Multitasking
Multitasking optimization is a recently introduced paradigm, focused on ...
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05/11/2020
On the Transferability of Knowledge among Vehicle Routing Problems by using a Cellular Evolutionary Multitasking
Multitasking optimization is a recently introduced paradigm, focused on ...
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05/08/2020
Transfer Learning and Online Learning for Traffic Forecasting under Different Data Availability Conditions: Alternatives and Pitfalls
This work aims at unveiling the potential of Transfer Learning (TL) for ...
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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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04/17/2020
Deep Echo State Networks for Short-Term Traffic Forecasting: Performance Comparison and Statistical Assessment
In short-term traffic forecasting, the goal is to accurately predict fut...
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04/14/2020
dMFEA-II: An Adaptive Multifactorial Evolutionary Algorithm for Permutation-based Discrete Optimization Problems
The emerging research paradigm coined as multitasking optimization aims ...
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03/27/2020
New Perspectives on the Use of Online Learning for Congestion Level Prediction over Traffic Data
This work focuses on classification over time series data. When a time s...
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03/25/2020
Plausible Counterfactuals: Auditing Deep Learning Classifiers with Realistic Adversarial Examples
The last decade has witnessed the proliferation of Deep Learning models ...
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03/24/2020
COEBA: A Coevolutionary Bat Algorithm for Discrete Evolutionary Multitasking
Multitasking optimization is an emerging research field which has attrac...
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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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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