Stochastic Forward Douglas-Rachford Splitting for Monotone Inclusions
نویسندگان
چکیده
We propose a stochastic Forward Douglas-Rachford Splitting framework for finding a zero point of the sum of three maximally monotone operators in real separable Hilbert space, where one of them is cocoercive. We first prove the weak almost sure convergence of the proposed method. We then characterize the rate of convergence in expectation in the case of strongly monotone operators. Finally, we provide numerical evidence to support the effectiveness of the method in Markovitz portfolio selection and support vector machines applications.
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