To significantly improve the online computation, we integrate the reduced mixed GMsFE basis methods with sparse tensor approximation and obtain a sparse representation for the model's outputs.
In the context of chemogenomics, some machine learning methods with sparse models have been proposed to detect informative combinations of drug chemical substructures and protein domains which may explain the mechanism of drug-target interactions.
Specific areas of interest relating to the methods used included the choice of outcome metric, methods of dealing with sparse events, heterogeneity, publication bias and use of individual patient data.
Therefore, the performance of a RANSAC-based method [8] for sparse point clouds is first investigated, and its drawbacks are analyzed in Section 2. Note that there exist methods that deal with sparse point clouds, but they can detect planes only such that textured planes are reconstructed [10].
In [23], a new principal component analysis method with nonnegative and sparse constraint is proposed, which is called NSPCA: (6).
Initial crystallization trials were performed at 293K using the hanging-drop vapour diffusion method with the Index sparse matrix crystallization kit (Hampton Research).
Student populations and injured cases were observed in all combination of strata of our three community measures and none of so-called extreme cells (defined above in methods) were empty or with sparse numbers of observation.
Whereas they considered a multi-class problem and developed its sparse version with ℓ2,1-norm regularization in their work, we reformulated its sparse method with elastic net penalization to suit our own needs.
In this paper, the technique of sparse representation is introduced into the spectral estimation, and a new compensation method is proposed, namely RBC with sparse representation (SR-RBC).
