14 citations · 15 across the 4 of their papers we have counts for
4 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…
Progress in Self-Certified Neural Networks
Maria Perez-Ortiz, Omar Rivasplata, Emilio Parrado-Hernandez +2
A learning method is self-certified if it uses all available data to simultaneously learn a predictor and certify its quality with a tight statistical certificate that is valid on…
PAC-Bayes bounds for stable algorithms with instance-dependent priors
Omar Rivasplata, Emilio Parrado-Hernandez, John Shawe-Taylor +2
PAC-Bayes bounds have been proposed to get risk estimates based on a training sample. In this paper the PAC-Bayes approach is combined with stability of the hypothesis learned by a…
State-Space Dynamics Distance for Clustering Sequential Data
Darío García-García, Emilio Parrado-Hernández, Fernando Díaz-de-María
This paper proposes a novel similarity measure for clustering sequential data. We first construct a common state-space by training a single probabilistic model with all the sequenc…