subproblems

The whole problem is transformed into a combination of projected subproblems , and problem solving in this space is more efficient.

An optimal solution to the problem could be constructed from optimal solutions to subproblems of the original problem.

We establish a quasi-Newton algorithm for solving a class of variational inequality problems which subproblems are linear equations.

These subproblems are then distributed to worker nodes, which solve the problem and return the results to the master node.

The three values below correspond, respectively, to the values returned by the three recursive subproblems I listed earlier.

In each example you'll somehow compare two sequences, and you'll use a two-dimensional table to store the solutions to subproblems.

All the subproblems, with are strongly monotone VIP and have a common structure, can be treated by one subroutine.

In the map step, the document is taken by the master node and the problem is divided into subproblems.

But because the sorting of the subproblems can be done in parallel, it parallelizes better than quick-sort.

Dynamic programming is used when recursion could be used but would be inefficient because it would repeatedly solve the same subproblems.

These two subproblems have important applications to numerical algebra, VLSI-layout and algorithm graph theory respectively;