This section presents a computable function for constraint set simplification, where computation is guaranteed to terminate by using the same criterion used in Sect.
◊ It has a time complexity that is linear in N and C. ◊ It is guaranteed to terminate [43] with a quadratic convergence rate [44].
On the other hand, as stated in Step 4, TPA problem is a single-variable convex optimization problem and therefore, any one-dimensional search is guaranteed to terminate when reaching the specified tolerance of ε 1.
As in the Euclidean domain, the "size" of the remainder ρ0 must be strictly smaller than β, and there must be only a finite number of possible sizes for ρ0, so that the algorithm is guaranteed to terminate.
Notice that this is a recursive procedure but is guaranteed to terminate, because (1) the number of concepts is finite; and (2) we assume that "Thing" is a common root for the two ontologies being aligned.
CG is guaranteed to terminate in n steps, the most time-consuming operation at each step being a matrix-vector product with a computational complexity proportional to the number of non-zero elements in L; in our setting L is very sparse, with 𝒪(n) non-zero elements, and CG terminates in fewer than 20 iterations.
The transformations are guaranteed to terminate and to map grammatically legal input to grammatically legal output.
He is guaranteed to be hired.
It is guaranteed to impress the world.
Third is guaranteeing to be in it.
None is guaranteed to work indefinitely.
