Spectral clustering is useful for a wide-ranging set of applications in areas such as biological data analysis, image processing and data mining. However, the computational and/or...
Ling Huang, Donghui Yan, Michael I. Jordan, Nina T...
We show attacks on several cryptographic schemes that have recently been proposed for achieving various security goals in sensor networks. Roughly speaking, these schemes all use ...
Martin Albrecht, Craig Gentry, Shai Halevi, Jonath...
The formidable difficulty in securing systems stems in large part from the increasing complexity of the systems we build but also the degree to which we now depend on information ...
Spectral clustering is one of the most widely used techniques for extracting the underlying global structure of a data set. Compressed sensing and matrix completion have emerged a...
We propose a family of clustering algorithms based on the maximization of dependence between the input variables and their cluster labels, as expressed by the Hilbert-Schmidt Inde...
Le Song, Alexander J. Smola, Arthur Gretton, Karst...