11 citations · 19 across the 5 of their papers we have counts for
5 papers
Adaptive Sparse Gaussian Process
Vanessa Gómez-Verdejo, Emilio Parrado-Hernández, Manel Martínez-Ramón
Adaptive learning is necessary for non-stationary environments where the learning machine needs to forget past data distribution. Efficient algorithms require a compact model updat…
Nonnegative OPLS for Supervised Design of Filter Banks: Application to Image and Audio Feature Extraction
Sergio Muñoz-Romero, Jerónimo Arenas García, Vanessa Gómez-Verdejo
Audio or visual data analysis tasks usually have to deal with high-dimensional and nonnegative signals. However, most data analysis methods suffer from overfitting and numerical pr…
Regularized Multivariate Analysis Framework for Interpretable High-Dimensional Variable Selection
Sergio Muñoz-Romero, Vanessa Gómez-Verdejo, Jerónimo Arenas-García
Multivariate Analysis (MVA) comprises a family of well-known methods for feature extraction which exploit correlations among input variables representing the data. One important pr…
A conditional one-output likelihood formulation for multitask Gaussian processes
Óscar García-Hinde, Vanessa Gómez-Verdejo, Manel Martínez-Ramón
Multitask Gaussian processes (MTGP) are the Gaussian process (GP) framework's solution for multioutput regression problems in which the elements of the regressors cannot be con…
Data Selection for Short Term load forecasting
Nestor Pereira, Miguel Angel Hombrados Herrera, Vanesssa Gómez-Verdejo +2
Power load forecast with Machine Learning is a fairly mature application of artificial intelligence and it is indispensable in operation, control and planning. Data selection techn…