This publication contributes to work in model selection, signal processing, with a focus reflected in its title: On the Identifiability of Latent Models for Dependent Data.
A new prediction-based objective function for gene selection is proposed, enabling the identification of small, interpretable models with high predictive power, outperforming alternatives while offering a network of models
This publication contributes to work in applied statistics, model selection, with a focus reflected in its title: Differentiating Inflammatory Bowel Diseases by Using Genomic Data: Dimension of the Problem and Network Organization.
This publication contributes to work in applied statistics, model selection, with a focus reflected in its title: A Paradigmatic Regression Algorithm for Gene Selection Problems.
This publication contributes to work in applied statistics, signal processing, model selection, with a focus reflected in its title: An Inertial Sensor Calibration Platform to Estimate and Select Error Models.
This publication contributes to work in applied statistics, signal processing, model selection, with a focus reflected in its title: Automatic and Computationally Efficient Method for Model Selection in Inertial Sensor Calibration.