The solution path of the generalized lasso
From MaRDI portal
Publication:638794
DOI10.1214/11-AOS878zbMath1234.62107arXiv1005.1971OpenAlexW3106348863MaRDI QIDQ638794
Ryan J. Tibshirani, Jonathan E. Taylor
Publication date: 14 September 2011
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1005.1971
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Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
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- Unnamed Item
- Unnamed Item
- Unnamed Item
- Nonlinear total variation based noise removal algorithms
- The solution path of the generalized lasso
- A compact formulation of an elastoplastic analysis problem
- Estimation of the mean of a multivariate normal distribution
- Least angle regression. (With discussion)
- Sparse regression with exact clustering
- Counting the faces of randomly-projected hypercubes and orthants, with applications
- Pathwise coordinate optimization
- On the ``degrees of freedom of the lasso
- Piecewise linear regularized solution paths
- NESTA: A Fast and Accurate First-Order Method for Sparse Recovery
- Outlier Detection Using Nonconvex Penalized Regression
- Adapting to Unknown Smoothness via Wavelet Shrinkage
- DASSO: Connections Between the Dantzig Selector and Lasso
- $\ell_1$ Trend Filtering
- Atomic Decomposition by Basis Pursuit
- Sparsity and Smoothness Via the Fused Lasso
- Analysis versus synthesis in signal priors
- Regularization and Variable Selection Via the Elastic Net
- Convergence of a block coordinate descent method for nondifferentiable minimization