And, we observe that the most important part of this exhaustive solution pertains to the combination of intervals, i.e., the combination of elements belonging to interval j of typical set λ n S n ℓ with elements belonging to interval k, k ≠ j typical set λ m S m ℓ, m ≠ n.
Our sensitivity analyses indicate that, under all the concurrent constraints considered, large deviations from the specified values of these critical parameters, and hence radically different solution characteristics, would not be expected, if an "exhaustive" solution search to the particular adaptation problem was attempted.
Results show BicPAM's superiority against its peers and its ability to retrieve unique types of biclusters of interest, to efficiently deliver exhaustive solutions and to successfully recover planted biclusters in datasets with varying levels of missing values and noise.
We have developed "Off-Spotter", a very fast and exhaustive algorithmic solution to the off-target discovery problem.
In the following, the proposed solution is compared to the optimal exhaustive solution for a special case with low users and RB number for evaluation.
Extended collective licensing by collective management organisations and similar mechanisms can make it possible to conclude agreements in those areas where collective licensing based on an authorisation by rightholders does not provide an exhaustive solution for covering all works or other subject matter to be used.
In addition, the use of molecular fragments, as often practiced in the de novo design of novel structures, can lead to a combinatorially large search space which becomes intractable for exhaustive solution techniques.
To get rid of this complexity, we point out that the above-mentioned ideal (exhaustive) solution can also be viewed as an exhaustive combination of intervals (J N combinations) associated with an exhaustive combination of elements within each interval combination (P N combinations).
The problem of training these models is an optimization task that can be solved with stochastic search methods (Saez-Rodriguez et al., 2009), which have the important limitation that they do not guarantee global optimality nor an exhaustive solution.
BicPAM approaches integrate existing disperse efforts towards pattern-based biclustering and provides the first critical strategies to efficiently discover exhaustive solutions of biclusters with shifting, scaling and symmetric assumptions with varying quality and underlying structures.
