Methodology - Machine learning
Miembros
Descripción
Desarrollo de metodologías de aprendizaje automático.
Publicaciones
- Boosting ridge for the extreme learning machine globally optimised for classification and regression problems
- Cluster analysis and forecasting of viruses incidence growth curves: Application to SARS-CoV-2
- Error-Correcting Output Codes in the Framework of Deep Ordinal Classification
- Activation functions for convolutional neural networks: proposals and experimental study
- Error-correcting output codes in the framework of deep ordinal classification
- An ordinal CNN approach for the assessment of neurological damage in Parkinson's disease patients
- Short- and long-term energy flux prediction using Multi-Task Evolutionary Artificial Neural Networks
- Machine learning methods in organ transplantation
- Ordinal multi-class architecture for predicting wind power ramp events based on reservoir computing
- Deep Ordinal Classification Based on the Proportional Odds Model
- Exploiting synthetically generated data with semi-supervised learning for small and imbalanced datasets
- Validation of multitask artificial neural networks to model desiccant wheels activated at low temperature
- Optimal Microgrid Topology Design and Siting of Distributed Generation Sources Using a Multi-Objective Substrate Layer Coral Reefs Optimization Algorithm
- A hybrid dynamic exploitation barebones particle swarm optimisation algorithm for time series segmentation
- On the use of evolutionary time series analysis for segmenting paleoclimate data
- Detection of early warning signals in paleoclimate data using a genetic time series segmentation algorithm
- Distribution-Based Discretisation and Ordinal Classification Applied to Wave Height Prediction
- Predicción ordinal de rampas de viento usando Echo State Networks de complejidad reducida
- Algoritmos de aprendizaje automático para predicción de niveles de niebla usando ventanas estáticas y dinámicas
- Clasificación ordinal de los grados de afectación de la enfermedad de Parkinson empleando imágenes de transportadores presinápticos de dopamina
