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Based on this analysis, we modify Andorra-I using a set of simple techniques that led to significantly better running time and scalability.
We summarize the number of multiplications required for DED, CD, and ED algorithms in Table 3. From this table, it was argued that the DED algorithm asymptotically should have a better running time than the CD algorithm.
This algorithm yields a better running time than that of the baseline algorithm in the previous section.
Our approach, fish-swarm logic regression, often outperforms other approaches in terms of the accuracy under different simulation configurations, and it has a better running time on parallel frameworks than that of the others.
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Experimental results indicate that our proposal yields a solution that is very close to the one found by applying the bisection method to a matrix with complete information, with better running times and a lower use of memory.
We can achieve much better running times if the number of involved subgraphs is small compared to the order of the original graph and the shortest path problems restricted to these subgraphs is computationally easy.
Regarding the application of decomposing molecule masses, this approach uses only one fifteenth of memory and shows better running times.
To achieve better running times, most tools try to identify promising pairs of sequences by applying word-based algorithms, which consider the frequency of common words in each pair of sequences [ 31].
It is worth noticing that contact maps that are better reconstructed require less running time.
The down side of using the better algorithms is their slower running time.
For future applications, the unimodularity of the integer linear programming formulation suggests to exploit this property more systematically, and eventually obtain an efficient algorithm for the topological alignment problem with better guaranteed bounds on the running time.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com