101. A stochastic inertial forward–backward splitting algorithm for multivariate monotone inclusions
- Author
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Silvia Villa, Bang Cong Vu, and Lorenzo Rosasco
- Subjects
Control and Optimization ,0211 other engineering and technologies ,Forward–backward algorithm ,010103 numerical & computational mathematics ,02 engineering and technology ,Management Science and Operations Research ,primal–dual algorithm ,01 natural sciences ,cocoercive operator ,composite operator ,duality ,forward–backward algorithm ,Monotone inclusion ,monotone operator ,operator splitting ,Applied Mathematics ,Pseudo-monotone operator ,symbols.namesake ,Convergence (routing) ,0101 mathematics ,Mathematics ,Sequence ,021103 operations research ,Hilbert space ,Strongly monotone ,Monotone polygon ,Convergence of random variables ,symbols ,Algorithm - Abstract
We propose an inertial forward–backward splitting algorithm to compute a zero of a sum of two monotone operators allowing for stochastic errors in the computation of the operators. More precisely, we establish almost sure convergence in real Hilbert spaces of the sequence of iterates to an optimal solution. Then, based on this analysis, we introduce two new classes of stochastic inertial primal–dual splitting methods for solving structured systems of composite monotone inclusions and prove their convergence. Our results extend to the stochastic and inertial setting various types of structured monotone inclusion problems and corresponding algorithmic solutions. Application to minimization problems is discussed.
- Published
- 2016