Pathwise coordinate optimization
| dc.creator | Friedman, Jerome | |
| dc.creator | Hastie, Trevor | |
| dc.creator | Höfling, Holger | |
| dc.creator | Tibshirani, Robert | |
| dc.date | 2007-08-10 | |
| dc.date | 2007-12-14 | |
| dc.date.accessioned | 2026-07-07T08:49:25Z | |
| dc.date.available | 2026-07-07T08:49:25Z | |
| dc.description | We consider ``one-at-a-time'' coordinate-wise descent algorithms for a class of convex optimization problems. An algorithm of this kind has been proposed for the $L_1$-penalized regression (lasso) in the literature, but it seems to have been largely ignored. Indeed, it seems that coordinate-wise algorithms are not often used in convex optimization. We show that this algorithm is very competitive with the well-known LARS (or homotopy) procedure in large lasso problems, and that it can be applied to related methods such as the garotte and elastic net. It turns out that coordinate-wise descent does not work in the ``fused lasso,'' however, so we derive a generalized algorithm that yields the solution in much less time that a standard convex optimizer. Finally, we generalize the procedure to the two-dimensional fused lasso, and demonstrate its performance on some image smoothing problems. | |
| dc.description | Published in at http://dx.doi.org/10.1214/07-AOAS131 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org) | |
| dc.identifier | https://arxiv.org/abs/0708.1485 | |
| dc.identifier | http://arxiv.org/abs/0708.1485 | |
| dc.identifier | Annals of Applied Statistics 2007, Vol. 1, No. 2, 302-332 | |
| dc.identifier | doi:10.1214/07-AOAS131 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/144290 | |
| dc.subject | Computation | |
| dc.subject | Optimization and Control | |
| dc.title | Pathwise coordinate optimization | |
| dc.type | text |