Continuation of Nesterov's Smoothing for Regression With Structured Sparsity in High-Dimensional Neuroimaging.
Fouad Hadj-SelemTommy LöfstedtElvis DohmatobVincent FrouinMathieu DuboisVincent GuillemotEdouard DuchesnayPublished in: IEEE Trans. Medical Imaging (2018)
Keyphrases
- structured sparsity
- high dimensional
- group lasso
- regression model
- variable selection
- statistical learning
- low dimensional
- model selection
- dimensionality reduction
- compressive sensing
- semidefinite programming
- learning problems
- linear regression
- regression problems
- estimation problems
- convex optimization problems
- high dimensionality
- gaussian processes
- dimension reduction
- high dimensional data
- data points
- regularization methods
- nearest neighbor
- linear models
- manifold learning
- linear programming
- feature space