Andrés Camero

Jeremy Eudaric

Heidi Kreibich

IEEE Geosci. Remote. Sens. Lett., 2024

An uncertainty-based objective function for hyperparameter optimization in Gaussian processes applied to expensive black-box problems.

[BibT_eX]

[DOI]

Appl. Soft Comput., 2024

2023

Providing AI expertise as an infrastructure in academia.

[BibT_eX]

[DOI]

Patterns, August, 2023

We Won't Get Fooled Again: When Performance Metric Malfunction Affects the Landscape of Hyperparameter Optimization Problems.

[BibT_eX]

[DOI]

Proceedings of the Optimization and Learning - 6th International Conference, 2023

2022

HPO: We won't get fooled again.

[BibT_eX]

[DOI]

CoRR, 2022

Landscape of Neural Architecture Search across sensors: how much do they differ ?

[BibT_eX]

[DOI]

CoRR, 2022

DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentation.

[BibT_eX]

[DOI]

Ariadna Pregel Hoderlein

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

A Data-driven Approach to Neural Architecture Search Initialization.

[BibT_eX]

[DOI]

CoRR, 2021

Fitness Landscape Footprint: A Framework to Compare Neural Architecture Search Problems.

[BibT_eX]

[DOI]

CoRR, 2021

Lessons from the Clustering Analysis of a Search Space: A Centroid-based Approach to Initializing NAS.

[BibT_eX]

[DOI]

CoRR, 2021

Reliable and Fast Recurrent Neural Network Architecture Optimization.

[BibT_eX]

[DOI]

CoRR, 2021

Bayesian neural architecture search using a training-free performance metric.

[BibT_eX]

[DOI]

Appl. Soft Comput., 2021

DENETHOR: The DynamicEarthNET dataset for Harmonized, inter-Operable, analysis-Ready, daily crop monitoring from space.

[BibT_eX]

[DOI]

Pierre-Philippe Mathieu

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Compact Neural Architecture Search for Local Climate Zones Classification.

[BibT_eX]

[DOI]

René Traoré

Xiaoxiang Zhu

Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

2020

Random error sampling-based recurrent neural network architecture optimization.

[BibT_eX]

[DOI]

Eng. Appl. Artif. Intell., 2020

2019

A Specialized Evolutionary Strategy Using Mean Absolute Error Random Sampling to Design Recurrent Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2019

JSDoop and TensorFlow.js: Volunteer Distributed Web Browser-Based Neural Network Training.

[BibT_eX]

[DOI]

José Á. Morell

IEEE Access, 2019

2018

Road map partitioning for routing by using a micro steady state evolutionary algorithm.

[BibT_eX]

[DOI]

Javier Arellano-Verdejo

Eng. Appl. Artif. Intell., 2018

DLOPT: Deep Learning Optimization Library.

[BibT_eX]

[DOI]

CoRR, 2018

Low-Cost Recurrent Neural Network Expected Performance Evaluation.

[BibT_eX]

[DOI]

CoRR, 2018

Evolutionary Deep Learning for Car Park Occupancy Prediction in Smart Cities.

[BibT_eX]

[DOI]

Proceedings of the Learning and Intelligent Optimization - 12th International Conference, 2018

Waste Generation Prediction in Smart Cities Through Deep Neuroevolution.

[BibT_eX]

[DOI]

Proceedings of the Smart Cities - First Ibero-American Congress, 2018

Comparing Deep Recurrent Networks Based on the MAE Random Sampling, a First Approach.

[BibT_eX]

[DOI]

Proceedings of the Advances in Artificial Intelligence, 2018

2017

Tile map size optimization for real world routing by using differential evolution.

[BibT_eX]

[DOI]

Javier Arellano-Verdejo

Christian Cintrano

Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017

2016

Using Evolutionary Algorithms to Find the Melody of a Musical Piece.

[BibT_eX]

[DOI]