Generalized Sparse Regularization with Application to fMRI Brain Decoding

[1]  Cees G. M. Snoek,et al.  Variable Selection , 2019, Model-Based Clustering and Classification for Data Science.

[2]  Ghassan Hamarneh,et al.  Generalized Sparse Classifiers for Decoding Cognitive States in fMRI , 2010, MLMI.

[3]  Bertrand Thirion,et al.  Multi-Class Sparse Bayesian Regression for Neuroimaging Data Analysis , 2010, MLMI.

[4]  Yongyi Yang,et al.  Machine Learning in Medical Imaging , 2010, IEEE Signal Processing Magazine.

[5]  Kaustubh Supekar,et al.  Sparse logistic regression for whole-brain classification of fMRI data , 2010, NeuroImage.

[6]  R. Tibshirani,et al.  The solution path of the generalized lasso , 2010, 1005.1971.

[7]  Yonina C. Eldar,et al.  Collaborative hierarchical sparse modeling , 2010, 2010 44th Annual Conference on Information Sciences and Systems (CISS).

[8]  T. Heskes,et al.  Efficient Bayesian multivariate fMRI analysis using a sparsifying spatio-temporal prior , 2010, NeuroImage.

[9]  Trevor Hastie,et al.  Regularization Paths for Generalized Linear Models via Coordinate Descent. , 2010, Journal of statistical software.

[10]  R. Tibshirani,et al.  A note on the group lasso and a sparse group lasso , 2010, 1001.0736.

[11]  Jürgen Hennig,et al.  Fully automated classification of HARDI in vivo data using a support vector machine , 2009, NeuroImage.

[12]  Jean-Philippe Vert,et al.  Group lasso with overlap and graph lasso , 2009, ICML '09.

[13]  A. Ravishankar Rao,et al.  Prediction and interpretation of distributed neural activity with sparse models , 2009, NeuroImage.

[14]  Michael P. Friedlander,et al.  Probing the Pareto Frontier for Basis Pursuit Solutions , 2008, SIAM J. Sci. Comput..

[15]  Masa-aki Sato,et al.  Sparse estimation automatically selects voxels relevant for the decoding of fMRI activity patterns , 2008, NeuroImage.

[16]  Tom Michael Mitchell,et al.  Predicting Human Brain Activity Associated with the Meanings of Nouns , 2008, Science.

[17]  P. Rossini,et al.  The role of the prefrontal cortex in sentence comprehension: An rTMS study , 2008, Cortex.

[18]  Jiawei Han,et al.  Spectral Regression: A Unified Approach for Sparse Subspace Learning , 2007, Seventh IEEE International Conference on Data Mining (ICDM 2007).

[19]  Jean-Baptiste Poline,et al.  Dealing with the shortcomings of spatial normalization: Multi‐subject parcellation of fMRI datasets , 2006, Human brain mapping.

[20]  M. Yuan,et al.  Model selection and estimation in regression with grouped variables , 2006 .

[21]  R. Tibshirani,et al.  Sparsity and smoothness via the fused lasso , 2005 .

[22]  Tom M. Mitchell,et al.  Learning to Decode Cognitive States from Brain Images , 2004, Machine Learning.

[23]  J. -B. Poline,et al.  Estimating the Delay of the fMRI Response , 2002, NeuroImage.

[24]  J. Mesirov,et al.  Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. , 1999, Science.

[25]  Richard S. J. Frackowiak,et al.  Functional anatomy of a common semantic system for words and pictures , 1996, Nature.

[26]  Stephen Lin,et al.  Graph Embedding and Extensions: A General Framework for Dimensionality Reduction , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[27]  R. Tibshirani Regression Shrinkage and Selection via the Lasso , 1996 .

[28]  J. Fodor The Modularity of mind. An essay on faculty psychology , 1986 .

[29]  © Institute of Mathematical Statistics, 2004 LEAST ANGLE REGRESSION , 2022 .