Stochastic Subspace Correction in Hilbert Space

We consider an incremental approximation method for solving variational problems in infinite-dimensional separable Hilbert spaces, where in each step a randomly and independently selected subproblem from an infinite collection of subproblems is solved. We show that convergence rates for the expectation of the squared error can be guaranteed under weaker conditions than previously established in Griebel and Oswald (Constr Approx 44(1):121–139, 2016).