Sentence examples for subclass of problem from inspiring English sources

There exist problems for which the most efficient known decision algorithm has exponential time complexity in the worst case (and in fact are known to be \ \textbf{NP}\ -hard in the general case – see Section 3.2) but which operate in polynomial time either in the average case or for a large subclass of problem instances of practical interest.

Most nonlinear programming algorithms are targeted to a particular subclass of problems.

This is particularly relevant for the subclass of problems in which we have access to the goal or to the highest value that a reward can take (e.g., reaching the center of a target, be as close as possible to a reference trajectory, etc).

The new method is much more efficient than previously derived RKN methods for some subclasses of problems.

We present the empirical evaluation of a system, Augur, that makes use of EVP metaknowledge to adapt its own domain knowledge in the context of a particular subclass of classification problem called Compositional Classification.

We define a subclass of such problems, termed highly coupled variable topology multi-body (HCVTMB) problems, where configuration and relative geometric sizes cause meshing changes in one body to propagate throughout much of the model.

Further analysis also shows that some subclasses of the problem correspond to a single elementary landscape.

Moreover, while LOH (Hobs = 0) markers (with sufficiently low MAF to escape detection from HWE deviation) have been shown to cause false associations in transmission-disequilibrium tests (Hirschhorn & Daly 2005), here we demonstrated that the effect of near-zero Hobs is only a subclass of the larger problem of near-zero MGF in GWAS.

Mathematical programs with equilibrium constraints (MPECs) form a relatively new and interesting subclass of nonlinear programming problems.

Minimum cost network design/dimensioning problems where feasibility has to be ensured w.r.t. a given (possibly infinite) set of scenarios of requirements form an important subclass of robust LP problems with right-hand side uncertainty.

Nonetheless, it is known that a significant subclass of \ \textbf{NP}\ -complete problems possess polynomial time approximation algorithms -- i.e. algorithms which are guaranteed to find a solution which is within a certain constant factor of optimality.