Stochastic Composite Least-Squares Regression with convergence rate O(1/n)

21 Feb 2017Nicolas FlammarionFrancis Bach

We consider the minimization of composite objective functions composed of the expectation of quadratic functions and an arbitrary convex function. We study the stochastic dual averaging algorithm with a constant step-size, showing that it leads to a convergence rate of O(1/n) without strong convexity assumptions... (read more)

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