Accelerated proximal stochastic dual coordinate ascent for regularized loss minimization
نویسندگان
چکیده
منابع مشابه
Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization
We introduce a proximal version of the stochastic dual coordinate ascent method and show how to accelerate the method using an inner-outer iteration procedure. We analyze the runtime of the framework and obtain rates that improve state-of-the-art results for various key machine learning optimization problems including SVM, logistic regression, ridge regression, Lasso, and multiclass SVM. Experi...
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ژورنال
عنوان ژورنال: Mathematical Programming
سال: 2014
ISSN: 0025-5610,1436-4646
DOI: 10.1007/s10107-014-0839-0