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The problem is these vastly powerful algorithmic engines are blackboxes.
We strive to answer two fundamental questions: what are the most powerful algorithmic principles for this task, and how does their performance depend on the amount of available eye movement data and the complexity of the target objects?
DESSCOM has two major components: (1) DESSCOM-MODEL, a modeling infrastructure comprising a library of carefully designed generic objects for modeling supply chain elements and dynamic interactions among these elements, and (2) DESSCOM-WORKBENCH, a decision workbench that can potentially include powerful algorithmic and simulation-based solution methods for supply chain decision-making.
Biclustering has emerged as a powerful algorithmic tool for analyzing gene expression data.
Biclustering has emerged as a powerful algorithmic tool for analyzing measurements of gene expression.
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This has led researchers to try combining different algorithmic components in order to design more powerful algorithms.
With today's powerful computing resources, algorithmic complexity and memory intensity may no more be an issue of concern.
So far a wide variety of great ideas and powerful approaches based on very different physical or algorithmic grounds were applied in order to solve this problem.
At the heart of these advances is the democratization of the use of the likelihood framework, which was made possible by algorithmic developments (Felsenstein, 1981) and the wide availability of powerful computing platforms.
This strategy, which attempts to alleviate algorithmic and reanalysis deficiencies, has the potential to become a powerful design tool.
On the other hand, the study of the problem (2.1) provides a unified framework for the development and analysis of algorithmic method and on the other hand it is a powerful tool for the study of first- and second-order optimality conditions in constrained optimality (see, for example, [1 7]).
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CEO of Professional Science Editing for Scientists @ prosciediting.com