Developer Guide for Intel® Data Analytics Acceleration Library 2019 Update 2
The iterative solver provides an iterative method to minimize an objective function that can be represented as a sum of functions:
Let S t be a set of intrinsic parameters of the iterative solver for updating the argument of the objective function. This set is the algorithm-specific and can be empty. The solver determines the choice of S 0.
To do the computations, iterate t from 1 until nIterations:
Choose a set of indices without replacement
Compute the gradient
Stop if
Compute
Update S t : S t = U(S t-1), where U is an algorithm-specific update of the set of intrinsic parameters.
The result of the solver is the argument
and a set of parameters
S
.
after the exit from
the loop.
You can resume the computations to get a more precise estimate of
the objective function minimum. To do this, pass to the algorithm the results
and
S
.
of the previous
run of the optimization solver. By default, the solver does not return the set
of intrinsic parameters. If you need it, set the
optionalResultRequired flag for the algorithm.