An iterative algorithm repeats a specific calculation, each iteration using the outputs from prior steps as its inputs, and produces a result in each step that converges to the desired value.
AlphaGo first studied 30m positions from expert games of go, absorbing information on the state of play from board data, and then played against itself across 50 computers, improving with each iteration, using a technique known as reinforcement learning.
Each iteration using Krotov's method requires two propagations.
Steady states are calculated by inexact Krylov-Newton iteration using ORTHORES and GMRES.
(lambda^{RM}_{h_{l}}) : the smallest eigenvalue obtained by the lth iteration using Algorithm 2M.
misfit distribution in the study area after final iteration using ModEM.
(lambda^{FM}_{h_{l}}) : the smallest eigenvalue obtained by the lth iteration using Algorithm 3M.
The algorithm flowchart of the recognition iteration using six interest zones is shown in Figure 13.
The clusters and the frames are repartitioned at each split iteration using k-means clustering.
The design points and the coefficients of the approximation polynomial are determined by numerical iteration using six moving points.
We propose a block Davidson-type subspace iteration using Chebyshev polynomial filters for large symmetric/hermitian eigenvalue problem.
