Publicaciones en las que colabora con Roberto Santana Hermida (57)

2024

  1. Factorized models in neural architecture search: Impact on computational costs and performance

    Proceedings of the International Joint Conference on Neural Networks

  2. Redefining Neural Architecture Search of Heterogeneous Multinetwork Models by Characterizing Variation Operators and Model Components

    IEEE Transactions on Neural Networks and Learning Systems, Vol. 35, Núm. 8, pp. 10561-10575

2023

  1. Analyzing the interplay between transferable GANs and gradient optimizers

    GECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion

  2. Neuroevolutionary algorithms driven by neuron coverage metrics for semi-supervised classification

    GECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion

2022

  1. A grammar-based GP approach applied to the design of deep neural networks

    Genetic Programming and Evolvable Machines, Vol. 23, Núm. 3, pp. 427-452

  2. Adversarial Perturbations for Evolutionary Optimization

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2021

  1. Automatic Design of Deep Neural Networks Applied to Image Segmentation Problems

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. Evolution of Gaussian Process kernels for machine translation post-editing effort estimation

    Annals of Mathematics and Artificial Intelligence, Vol. 89, Núm. 8-9, pp. 835-856

  3. Evolving Gaussian process kernels from elementary mathematical expressions for time series extrapolation

    Neurocomputing, Vol. 462, pp. 426-439

  4. In-depth analysis of SVM kernel learning and its components

    Neural Computing and Applications, Vol. 33, Núm. 12, pp. 6575-6594

  5. On the exploitation of neuroevolutionary information

    GECCO 2021 Companion - Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion

  6. Towards automatic construction of multi-network models for heterogeneous multi-task learning

    ACM Transactions on Knowledge Discovery from Data, Vol. 15, Núm. 2

2020

  1. A Symmetric grammar approach for designing segmentation models

    2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings

  2. Analysis of the transferability and robustness of GANs evolved for Pareto set approximations

    Neural Networks, Vol. 132, pp. 281-296

  3. Automatic structural search for multi-task learning VALPs

    Communications in Computer and Information Science

  4. Bayesian Optimization Approaches for Massively Multi-modal Problems

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  5. Envisioning the Benefits of Back-Drive in Evolutionary Algorithms

    2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings

  6. EvoFlow: A Python library for evolving deep neural network architectures in tensorflow

    2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020

  7. Evolving Gaussian Process Kernels for Translation Editing Effort Estimation

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2019

  1. An Experimental Study in Adaptive Kernel Selection for Bayesian Optimization

    IEEE Access, Vol. 7, pp. 184294-184302