Background Providers have been reluctant to disclose patient data for public-health purposes. Even if patient privacy is ensured, the desire to protect provider confidentiality h...
Khaled El Emam, Jun Hu, Jay Mercer, Liam Peyton, M...
In high dimensional data, the general performance of traditional clustering algorithms decreases. This is partly because the similarity criterion used by these algorithms becomes ...
We consider clustering situations in which the pairwise affinity between data points depends on a latent ”context” variable. For example, when clustering features arising fro...
Most current network intrusion detection systems employ signature-based methods or data mining-based methods which rely on labelled training data. This training data is typically ...
Abstract. The problem of clustering data can be formulated as a graph partitioning problem. In this setting, spectral methods for obtaining optimal solutions have received a lot of...
Marcus Weber, Wasinee Rungsarityotin, Alexander Sc...