Intel® oneAPI Data Analytics Library Developer Guide and Reference
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Iterative Solver
The iterative solver provides an iterative method to minimize an objective function that can be represented as a sum of functions in composite form

where:
,
, where
is a convex, continuously differentiable
(smooth) functions,
is a convex, non-differentiable (non-smooth) function
The Algorithmic Framework of an Iterative Solver
All solvers presented in the library follow a common algorithmic framework. Let 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
.
To do the computations, iterate t from 1 until :
Choose a set of indices without replacement
,
,
, where b is the batch size.
Compute the gradient
where
Convergence check:
Stop if
where U is an algorithm-specific vector (argument or gradient) and d is an algorithm-specific power of Lebesgue space
Compute
using the algorithm-specific transformation T that updates the function’s argument:
Update
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
after the exit from the loop.


Iterative solvers