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CORR
2011
Springer

Parallel Coordinate Descent for L1-Regularized Loss Minimization

13 years 3 months ago
Parallel Coordinate Descent for L1-Regularized Loss Minimization
We propose Shotgun, a parallel coordinate descent algorithm for minimizing L1regularized losses. Though coordinate descent seems inherently sequential, we prove convergence bounds for Shotgun which predict linear speedups, up to a problemdependent limit. We present a comprehensive empirical study of Shotgun for Lasso and sparse logistic regression. Our theoretical predictions on the potential for parallelism closely match behavior on real data. Shotgun outperforms other published solvers on a range of large problems, proving to be one of
Joseph K. Bradley, Aapo Kyrola, Danny Bickson, Car
Added 19 Aug 2011
Updated 19 Aug 2011
Type Journal
Year 2011
Where CORR
Authors Joseph K. Bradley, Aapo Kyrola, Danny Bickson, Carlos Guestrin
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