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Our simulation results indicate that reinforced BP CS schemes offer very good complexity performance tradeoffs for very sparse signal vectors.
Algorithms solving the problem exactly have been designed but the running time is improved over trivial brute-force solutions only for very sparse instances.
Consequently, LIHT is suitable for very sparse signals.
This works well for very sparse networks with unguided or random routing protocols.
Unlike the TV-regularized methods, our model has the advantage that it performs well for very sparse data sets.
We solve several implementation challenges to boost its efficiency on modern computer architectures, specifically for very sparse adjacency matrices that represent a wide range of social networks.
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However, statistical fluctuations in the data largely accounts for the observed inconsistency of very sparse projections (see the Discussion section).
The following analysis indicates that statistical fluctuation due to sampling errors can largely account for the observed inconsistency of very sparse projections.
"Duck" is rated PG-13 (Parents strongly cautioned) for a very sparse smattering of bad language.
For a very sparse probability density function, Hyvärinen [20] used the following function to represent a sparse distribution: (14).
Here we describe a new approach for comparing very sparse DNA sequence data from two samples that differs from existing methods in two important ways.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com