The combined information in Figures 2 and 3 illustrates that a substantial degree of structure in the DSE can be accreted while still within the 95% confidence interval of accepted random coil values, a result consistent with computational projections (38).
In a previous work we developed a computational method called projection to latent pathways (PLP), which was conceived to maximize covariance between envirome and fluxome data under the constraint of metabolic network elementary flux modes (EFM).
In order to reduce the computational complexity, the projection-based greedy (PBG) algorithm [22] assumes that the insertion of a new stream does not significantly alter the SNIR of already scheduled streams.
Efforts for deducing the computational costs in computing the projection have been made by using penalty function methods or relaxing the constrained convex set by polyhedral convex ones; see, e.g., [6 15].
However, the computational difficulty of the projection might seriously affect the efficiency of the method.
Owing to high computational efficiency and nonlinear projection ability of using kernel functions, kernel methods are applied to extend the traditional linear model for feature selection and fusion.
To balance locality and computational efficiency, the hash projection matrix of each instance is parameterized, with guaranteed approximation error bound, as a linear combination of basis hash projections associated with a small set of anchor points.
By taking into account the high computational efficiency and nonlinear projection ability of kernel functions, a kernel factor analysis is investigated for feature selection and representation in gearbox condition monitoring.
The high computational cost of the projection operator P M and P S should account for the slower imaging speed of the RAAR-l 0 algorithm and the RAAR-l 1 algorithm.
Indeed, by localizing the projection, computations remain on the element level, reducing the computational cost relative to Eq. (25).
