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Discovering cluster structure in multi-view data has become a hot research topic and significant progress has been made in multi-view clustering.
Discovering cluster structures by random walks on the diffusion model is attributed to the spectral graph theory that solves the eigenvectors of Laplacian matrix [27], [28].
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Handling the first challenge is to escape the circular dependency between detecting meaningful subspaces and discovering clusters.
We use graph partitioning and community detection as the basis for discovering clusters of RSF-attacked sensors.
In contrast to the existing density-based clustering algorithms, our algorithm has the ability of discovering clusters according to non-spatial, spatial and temporal values of the objects.
While most of SEED's utilities fall into the preprocessing area of NGS data, our tests also demonstrate its efficiency as stand-alone tool for discovering clusters of small RNA sequences in NGS data from unsequenced organisms.
The newly discovered cluster was born when the universe was only half that age.
If the considered clustering algorithm would work perfectly, then for each discovered cluster j, it would exist a real cluster i exactly coinciding with j.
A couple of years ago, I discovered Cluster Busters, a ground that advocates the use of alternative (though, sadly, illegal) cluster treatments.
It's usually just tanks and fighter jets being shipped off to repress dissent and arm child soldiers, in the past people have been able to find weapons that specifically violate UK law: In previous years Amnesty International has discovered cluster bombs, electric stun batons, shock irons and gang chain.
Such a neural network might be used in data mining, for example, to discover clusters of customers in a marketing data warehouse.
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