A Fast and Flexible Algorithm for the Graph-Fused Lasso
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[1] H. Fleischner. Eulerian graphs and related topics , 1990 .
[2] L. Rudin,et al. Nonlinear total variation based noise removal algorithms , 1992 .
[3] D. West. Introduction to Graph Theory , 1995 .
[4] Yurii Nesterov,et al. Smooth minimization of non-smooth functions , 2005, Math. Program..
[5] R. Tibshirani,et al. Sparsity and smoothness via the fused lasso , 2005 .
[6] Antonin Chambolle,et al. On Total Variation Minimization and Surface Evolution Using Parametric Maximum Flows , 2009, International Journal of Computer Vision.
[7] Xi Chen,et al. Smoothing proximal gradient method for general structured sparse regression , 2010, The Annals of Applied Statistics.
[8] R. Tibshirani,et al. A note on the group lasso and a sparse group lasso , 2010, 1001.0736.
[9] R. Tibshirani,et al. The solution path of the generalized lasso , 2010, 1005.1971.
[10] Stephen P. Boyd,et al. Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers , 2011, Found. Trends Mach. Learn..
[11] Timothy A. Davis,et al. The university of Florida sparse matrix collection , 2011, TOMS.
[12] Stephen P. Boyd,et al. An ADMM Algorithm for a Class of Total Variation Regularized Estimation Problems , 2012, 1203.1828.
[13] Nicholas A. Johnson,et al. A Dynamic Programming Algorithm for the Fused Lasso and L 0-Segmentation , 2013 .
[14] Ryan J. Tibshirani,et al. Fast and Flexible ADMM Algorithms for Trend Filtering , 2014, ArXiv.
[15] Michael I. Jordan,et al. A General Analysis of the Convergence of ADMM , 2015, ICML.
[16] Oluwasanmi Koyejo,et al. False Discovery Rate Smoothing , 2014, Journal of the American Statistical Association.