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» Set cover algorithms for very large datasets
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RAID
2004
Springer
15 years 11 months ago
HoneyStat: Local Worm Detection Using Honeypots
Worm detection systems have traditionally used global strategies and focused on scan rates. The noise associated with this approach requires statistical techniques and large data s...
David Dagon, Xinzhou Qin, Guofei Gu, Wenke Lee, Ju...
BMCBI
2010
112views more  BMCBI 2010»
15 years 6 months ago
In silico fragmentation for computer assisted identification of metabolite mass spectra
Background: Mass spectrometry has become the analytical method of choice in metabolomics research. The identification of unknown compounds is the main bottleneck. In addition to t...
Sebastian Wolf, Stephan Schmidt, Matthias Mül...
ECCV
2008
Springer
16 years 8 months ago
Continuous Energy Minimization Via Repeated Binary Fusion
Abstract. Variational problems, which are commonly used to solve lowlevel vision tasks, are typically minimized via a local, iterative optimization strategy, e.g. gradient descent....
Werner Trobin, Thomas Pock, Daniel Cremers, Horst ...
ISBI
2008
IEEE
16 years 16 days ago
An optimal-path approach for neural circuit reconstruction
Neurobiologists are collecting large amounts of electron microscopy image data to gain a better understanding of neuron organization in the central nervous system. Image analysis ...
Elizabeth Jurrus, Ross T. Whitaker, Bryan W. Jones...
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ICASSP
2011
IEEE
14 years 10 months ago
Co-clustering as multilinear decomposition with sparse latent factors
The K-means clustering problem seeks to partition the columns of a data matrix in subsets, such that columns in the same subset are ‘close’ to each other. The co-clustering pr...
Evangelos E. Papalexakis, Nicholas D. Sidiropoulos