  In this paper we propose a stochastic primal dual fixed point method (SPDFP)
for solving the sum of two proper lower semi-continuous convex function and one
of which is composite. The method is based on the primal dual fixed point
method (PDFP) proposed in [7] that does not require subproblem solving. Under
some mild condition, the convergence is established based on two sets of
assumptions: bounded and unbounded gradients and the convergence rate of the
expected error of iterate is of the order O(k^{\alpha}) where k is iteration
number and \alpha \in (0, 1]. Finally, numerical examples on graphic Lasso and
logistic regressions are given to demonstrate the effectiveness of the proposed
algorithm.
