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Found 3 papers, 0 papers with code
Consistency of Lloyd's Algorithm Under Perturbations
In canonical settings with ground truth clusters, we derive bounds for algorithms such as $k$-means$++$ to find good initializations and thus leading to the correctness of clustering via the main result.
Community detection using low-dimensional network embedding algorithms
With the increasing relevance of large networks in important areas such as the study of contact networks for spread of disease, or social networks for their impact on geopolitics, it has become necessary to study machine learning tools that are scalable to very large networks, often containing millions of nodes.
A testing based extraction algorithm for identifying significant communities in networks
In addition, we carry out a simulation study to assess the effectiveness of ESSC in networks with various types of community structure, including networks with overlapping communities and those with background vertices.
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