Multiscale Mining of fMRI Data with Hierarchical Structured Sparsity

DOI10.1137/110832380zbMath1263.90059DBLPjournals/siamis/JenattonGMOEBT12arXiv1105.0363OpenAlexW2059742622WikidataQ55214465 ScholiaQ55214465MaRDI QIDQ4902145

Guillaume Obozinski, Francis Bach, Bertrand Thirion, Alexandre Gramfort, Evelyn Eger, Rodolphe Jenatton, Vincent Michel

Publication date: 25 January 2013

Published in: SIAM Journal on Imaging Sciences (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1105.0363

zbMATH Keywords

proximal methodsstructured sparsitybrain readingintersubject validationsparse hierarchical models

Mathematics Subject Classification ID

Multivariate analysis (62H99) Ridge regression; shrinkage estimators (Lasso) (62J07) Applications of statistics to biology and medical sciences; meta analysis (62P10) Ill-posedness and regularization problems in numerical linear algebra (65F22) Convex programming (90C25)

Related Items (4)

Linearized alternating direction method of multipliers for sparse group and fused Lasso models ⋮ Minimum distance Lasso for robust high-dimensional regression ⋮ Structured Sparsity: Discrete and Convex Approaches ⋮ Structured sparsity through convex optimization

Uses Software

• MayaVi
• Mayavi
• UNLocBoX

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