419 citations · 3.1k across the 71 of their papers we have counts for
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stat.ML2013★ 14 cited
Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization
Shai Shalev-Shwartz, Tong Zhang
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 runti…
stat.ML2013★ 59 cited
Accelerated Mini-Batch Stochastic Dual Coordinate Ascent
Shai Shalev-Shwartz, Tong Zhang
Stochastic dual coordinate ascent (SDCA) is an effective technique for solving regularized loss minimization problems in machine learning. This paper considers an extension of SDCA…