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Stochastic Coordinate Descent Methods for Regularized Smooth and Nonsmooth Losses
[chapter]
2012
Lecture Notes in Computer Science
Stochastic Coordinate Descent (SCD) methods are among the first optimization schemes suggested for efficiently solving large scale problems. However, until now, there exists a gap between the convergence rate analysis and practical SCD algorithms for general smooth losses and there is no primal SCD algorithm for nonsmooth losses. In this paper, we discuss these issues using the recently developed structural optimization techniques. In particular, we first present a principled and practical SCD
doi:10.1007/978-3-642-33460-3_40
fatcat:oj35t52xtvh6pj4do77d7h7ltq