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Found 5 papers, 2 papers with code
Functional Graph Convolutional Networks: A unified multi-task and multi-modal learning framework to facilitate health and social-care insights
This paper introduces a novel Functional Graph Convolutional Network (funGCN) framework that combines Functional Data Analysis and Graph Convolutional Networks to address the complexities of multi-task and multi-modal learning in digital health and longitudinal studies.
A new computationally efficient algorithm to solve Feature Selection for Functional Data Classification in high-dimensional spaces
This paper introduces a novel methodology for Feature Selection for Functional Classification, FSFC, that addresses the challenge of jointly performing feature selection and classification of functional data in scenarios with categorical responses and multivariate longitudinal features.
FAStEN: an efficient adaptive method for feature selection and estimation in high-dimensional functional regressions
Functional regression analysis is an established tool for many contemporary scientific applications.
A Highly-Efficient Group Elastic Net Algorithm with an Application to Function-On-Scalar Regression
Feature Selection and Functional Data Analysis are two dynamic areas of research, with important applications in the analysis of large and complex data sets.
An Efficient Semi-smooth Newton Augmented Lagrangian Method for Elastic Net
Our new algorithm exploits both the sparsity induced by the Elastic Net penalty and the sparsity due to the second order information of the augmented Lagrangian.
