Category:Homotopy
From SparseSolver
Homotopy methods follow a regularization path and add one component at a time. For very sparse solutions, this can be efficient. When the solutions are not very sparse, these methods are generally not competitive with alternative solvers.
For the BP problem, solvers include LARS[1] and Homotopy[2]. Good implementations are part of the L1 Homotopy toolbox from Salman Asif and Justin Romberg.
For the Dantzig problem, solvers include DASSO[3]
References
- ↑ B. Efron, T. Hastie, I. Johnstone, and R. Tibshirani, Least angle regression, Ann. Statist. 32 (2004), no. 2, 407--499. link
- ↑ M. R. Osborne, B. Presnell, and B. A. Turlach, A new approach to variable selection in least squares problems, IMA J. Numer. Anal. 20 (2000), no. 3, 389--403.
- ↑ G. James, P. Radchenko, and J. Lv, DASSO: Connections Between the Dantzig Selector and Lasso, J. Roy. Statist. Soc., Ser. B 71 (2009), 127--142.
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