The phrase "mainstream algorithm" is correct and can be used in written English.
It refers to a commonly used and widely accepted algorithm in a certain field or industry. Example: "Google's search engine uses a mainstream algorithm to determine the most relevant results for a user's search query."
Mainstream algorithms for deciding network consistency are based on searching for network refinements whose consistency is known to be tractable, either directly or by using a SAT solver.
The two-step algorithm and the best worst case analysis represent two mainstream algorithms that are computationally efficient in obtaining interval solutions for an IMP model.
The two-step algorithm and the best worst case analysis represent two mainstream algorithms that are computationally efficient in obtaining interval solutions for an IMP model (Rosenberg [2009]; Fan and Huang [2012]).
We introduce a novel generalization of discrete AdaBoost which departs from this mainstream of algorithms.
We show here that mainstream inference algorithms based on jointrees are a special case of the approach based on multi-linear functions, in a very precise sense.
The proposed method was applied to ten multiclass gene-expression datasets; the independent test accuracy and generalization performance were obviously better than those of mainstream comparative algorithms.
But from a mainstream video, the algorithm often takes a sharp turn to suggest extremist ideas.
The originality of the study is to investigate the promoted percentages of the Extreme Learning Machines by those mainstream signal decomposing algorithms in the multiple step wind speed forecasting.
In mitigation though, mainstream sequence search algorithms like BLAST [ 9, 10] and HMMER [ 11, 12] deploy compositional bias statistics [ 13– 15] to suppress some classes of remnant segments (e.g., low-complexity sequence).
Broadcast algorithms of mainstream MPI implementations, MPICH and Open MPI, are modeled and analyzed.
