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KDD
2006
ACM
145views Data Mining» more  KDD 2006»
14 years 6 months ago
Deriving quantitative models for correlation clusters
Correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a comm...
Arthur Zimek, Christian Böhm, Elke Achtert, H...
ICML
2010
IEEE
13 years 7 months ago
Projection Penalties: Dimension Reduction without Loss
Dimension reduction is popular for learning predictive models in high-dimensional spaces. It can highlight the relevant part of the feature space and avoid the curse of dimensiona...
Yi Zhang 0010, Jeff Schneider
MICCAI
2010
Springer
13 years 4 months ago
Generalized Sparse Classifiers for Decoding Cognitive States in fMRI
The high dimensionality of functional magnetic resonance imaging (fMRI) data presents major challenges to fMRI pattern classification. Directly applying standard classifiers often ...
Bernard Ng, Arash Vahdat, Ghassan Hamarneh, Rafeef...
DATAMINE
2008
95views more  DATAMINE 2008»
13 years 4 months ago
A dynamic bibliometric model for identifying online communities
Predictive modelling of online dynamic user-interaction recordings and community identifi cation from such data b ecomes more and more imp ortant w ith th e w idesp read use of on...
Xin Wang, Ata Kabán
SIGSOFT
2007
ACM
14 years 7 months ago
Measuring empirical computational complexity
The standard language for describing the asymptotic behavior of algorithms is theoretical computational complexity. We propose a method for describing the asymptotic behavior of p...
Simon Goldsmith, Alex Aiken, Daniel Shawcross Wilk...