127 citations · 176 across the 16 of their papers we have counts for
18 papers
Enabling Population-Based Architectures for Neural Combinatorial Optimization
Andoni Irazusta Garmendia, Josu Ceberio, Alexander Mendiburu
Neural Combinatorial Optimization (NCO) has mostly focused on learning policies, typically neural networks, that operate on a single candidate solution at a time, either by constru…
MARCO: A Memory-Augmented Reinforcement Framework for Combinatorial Optimization
Andoni I. Garmendia, Quentin Cappart, Josu Ceberio +1
Neural Combinatorial Optimization (NCO) is an emerging domain where deep learning techniques are employed to address combinatorial optimization problems as a standalone solver. Des…
Light up that Droid! On the Effectiveness of Static Analysis Features against App Obfuscation for Android Malware Detection
Borja Molina-Coronado, Antonio Ruggia, Usue Mori +3
Malware authors have seen obfuscation as the mean to bypass malware detectors based on static analysis features. For Android, several studies have confirmed that many anti-malware…
Efficient Concept Drift Handling for Batch Android Malware Detection Models
Molina-Coronado B., Mori U., Mendiburu A. +1
The rapidly evolving nature of Android apps poses a significant challenge to static batch machine learning algorithms employed in malware detection systems, as they quickly become…
Neuroevolutionary algorithms driven by neuron coverage metrics for semi-supervised classification
Roberto Santana, Ivan Hidalgo-Cenalmor, Unai Garciarena +2
In some machine learning applications the availability of labeled instances for supervised classification is limited while unlabeled instances are abundant. Semi-supervised learnin…
Neural Improvement Heuristics for Graph Combinatorial Optimization Problems
Andoni I. Garmendia, Josu Ceberio, Alexander Mendiburu
Recent advances in graph neural network architectures and increased computation power have revolutionized the field of combinatorial optimization (CO). Among the proposed models fo…