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This is important in designing appropriately powered investigations and in managing expectations as to what can be achieved with sparse data.
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It is now clear that this can be achieved with a relatively sparse data sets (eg [50]).
By compressing the original high-dimensional sparse BoI vectors into compact binary descriptors, over 100 × speed up can be achieved with sacrificing 0.05 precision at 0.30 recall.
Because this is achieved with a simple modeling framework, one can investigate large networks with relatively sparse data compared to other formalisms for modeling of signaling networks [ 12, 17, 45, 46].
After full-atom refinement, RosettaEPR yielded a 1.7 Å model of T4-lysozyme, thus indicating that atomic detail models can be achieved by combining sparse EPR data with Rosetta.
The 3D geomechanical earth model demonstrates that (1) the distribution of rock properties depends on formation lithology and (2) high lateral and vertical resolution can be achieved even in the areas with sparse wellbore information.
This indicates that maximum fluorescence intensity is achieved at sparse labeling with ∼30 dyes per particle; as the dye density increases, fluorescence quenching occurs, reducing the overall emission intensity.
The best cross-validation accuracy is 79.82 ± 1.67%, which is achieved by sparse logistic regression with logistic loss and 90% of data as training.
Alternatively, sparse recovery can be achieved via greedy algorithms.
l0 minimization based sparse reconstruction is an NP-hard problem with very high computational complexity, which is difficult to be achieved by traditional algorithms.
For magnetite, an excellent representation of the experimental tracer data is achieved together with a satisfactory description of the sparse chemical diffusion data available.
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