The joint lasso: high-dimensional regression for group structured data
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[1] Joe W. Gray,et al. Joint estimation of multiple networks from time course data , 2013 .
[2] R. Tibshirani,et al. Sparsity and smoothness via the fused lasso , 2005 .
[3] R. Tibshirani,et al. Sparse inverse covariance estimation with the graphical lasso. , 2008, Biostatistics.
[4] Yurii Nesterov,et al. Smooth minimization of non-smooth functions , 2005, Math. Program..
[5] J. Davis. Bioinformatics and Computational Biology Solutions Using R and Bioconductor , 2007 .
[6] M. Weiner,et al. Neuroimaging markers for the prediction and early diagnosis of Alzheimer's disease dementia , 2011, Trends in Neurosciences.
[7] Michael W. Weiner,et al. Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease , 2016, Alzheimer's & Dementia.
[8] Torsten Hothorn,et al. A unified framework of constrained regression , 2014, Stat. Comput..
[9] Patrick Danaher,et al. The joint graphical lasso for inverse covariance estimation across multiple classes , 2011, Journal of the Royal Statistical Society. Series B, Statistical methodology.
[10] Trevor Hastie,et al. Regularization Paths for Generalized Linear Models via Coordinate Descent. , 2010, Journal of statistical software.
[11] Gordon K. Smyth,et al. limma: Linear Models for Microarray Data , 2005 .
[12] Guangchuang Yu,et al. clusterProfiler: an R package for comparing biological themes among gene clusters. , 2012, Omics : a journal of integrative biology.
[13] Xi Chen,et al. Graph-Structured Multi-task Regression and an Efficient Optimization Method for General Fused Lasso , 2010, ArXiv.
[14] M. Yuan,et al. Model selection and estimation in regression with grouped variables , 2006 .
[15] L. Wasserman,et al. HIGH DIMENSIONAL VARIABLE SELECTION. , 2007, Annals of statistics.
[16] Holger Hoefling. A Path Algorithm for the Fused Lasso Signal Approximator , 2009, 0910.0526.
[17] Johann S. Hawe,et al. Crowdsourced analysis of clinical trial data to predict amyotrophic lateral sclerosis progression , 2014, Nature Biotechnology.
[18] Sach Mukherjee,et al. Two-Sample Testing in High-Dimensional Models , 2012 .
[19] Matthew E Ritchie,et al. Integrative analysis of RUNX1 downstream pathways and target genes , 2008, BMC Genomics.
[20] Ben Taskar,et al. Joint covariate selection and joint subspace selection for multiple classification problems , 2010, Stat. Comput..
[21] C. Jack,et al. Ways toward an early diagnosis in Alzheimer’s disease: The Alzheimer’s Disease Neuroimaging Initiative (ADNI) , 2005, Alzheimer's & Dementia.
[22] Adam A. Margolin,et al. The Cancer Cell Line Encyclopedia enables predictive modeling of anticancer drug sensitivity , 2012, Nature.
[23] R. Tibshirani,et al. A SIGNIFICANCE TEST FOR THE LASSO. , 2013, Annals of statistics.
[24] Sach Mukherjee,et al. Two-sample testing in high dimensions , 2017 .
[25] Jieping Ye,et al. An efficient algorithm for a class of fused lasso problems , 2010, KDD.
[26] Xiaohui Xie,et al. Split Bregman method for large scale fused Lasso , 2010, Comput. Stat. Data Anal..
[27] 中尾 光輝,et al. KEGG(Kyoto Encyclopedia of Genes and Genomes)〔和文〕 (特集 ゲノム医学の現在と未来--基礎と臨床) -- (データベース) , 2000 .
[28] Jim Q. Smith,et al. Exact estimation of multiple directed acyclic graphs , 2014, Stat. Comput..
[29] R. Tibshirani,et al. PATHWISE COORDINATE OPTIMIZATION , 2007, 0708.1485.