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06/16/2023
Structural Restricted Boltzmann Machine for image denoising and classification
Restricted Boltzmann Machines are generative models that consist of a la...
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03/05/2023
Neuroevolutionary algorithms driven by neuron coverage metrics for semi-supervised classification
In some machine learning applications the availability of labeled instan...
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02/15/2023
On the Hyperparameters influencing a PINN's generalization beyond the training domain
Physics-Informed Neural Networks (PINNs) are Neural Network architecture...
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07/05/2021
When and How to Fool Explainable Models (and Humans) with Adversarial Examples
Reliable deployment of machine learning models such as neural networks c...
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06/16/2021
Redefining Neural Architecture Search of Heterogeneous Multi-Network Models by Characterizing Variation Operators and Model Components
With neural architecture search methods gaining ground on manually desig...
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05/26/2021
On the Exploitation of Neuroevolutionary Information: Analyzing the Past for a More Efficient Future
Neuroevolutionary algorithms, automatic searches of neural network struc...
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12/28/2020
Analysis of Dominant Classes in Universal Adversarial Perturbations
The reasons why Deep Neural Networks are susceptible to being fooled by ...
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04/14/2020
Extending Adversarial Attacks to Produce Adversarial Class Probability Distributions
Despite the remarkable performance and generalization levels of deep lea...
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01/23/2020
On the human evaluation of audio adversarial examples
Human-machine interaction is increasingly dependent on speech communicat...
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11/22/2019
Universal adversarial examples in speech command classification
Adversarial examples are inputs intentionally perturbed with the aim of ...
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03/21/2019
Towards automatic construction of multi-network models for heterogeneous multi-task learning
Multi-task learning, as it is understood nowadays, consists of using one...
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06/04/2018
On the performance of multi-objective estimation of distribution algorithms for combinatorial problems
Fitness landscape analysis investigates features with a high influence o...
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01/13/2018
Towards a more efficient representation of imputation operators in TPOT
Automated Machine Learning encompasses a set of meta-algorithms intended...
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07/11/2017
Gray-box optimization and factorized distribution algorithms: where two worlds collide
The concept of gray-box optimization, in juxtaposition to black-box opti...
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06/04/2017
Evolving imputation strategies for missing data in classification problems with TPOT
Missing data has a ubiquitous presence in real-life applications of mach...
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02/18/2017
Reproducing and learning new algebraic operations on word embeddings using genetic programming
Word-vector representations associate a high dimensional real-vector to ...
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08/17/2016
Evolutionary Approaches to Optimization Problems in Chimera Topologies
Chimera graphs define the topology of one of the first commercially avai...
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12/10/2015
Computing factorized approximations of Pareto-fronts using mNM-landscapes and Boltzmann distributions
NM-landscapes have been recently introduced as a class of tunable rugged...
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11/18/2015