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» Data Mining from Functional Brain Images
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KDD
2005
ACM
161views Data Mining» more  KDD 2005»
16 years 6 months ago
Combining email models for false positive reduction
Machine learning and data mining can be effectively used to model, classify and discover interesting information for a wide variety of data including email. The Email Mining Toolk...
Shlomo Hershkop, Salvatore J. Stolfo
MICCAI
2009
Springer
16 years 7 months ago
Multiple Q-Shell ODF Reconstruction in Q-Ball Imaging
Q-ball imaging (QBI) is a high angular resolution diffusion imaging (HARDI) technique which has been proven very successful in resolving multiple intravoxel fiber orientations in M...
Iman Aganj, Christophe Lenglet, Guillermo Sapiro...
ICAI
2004
15 years 7 months ago
A Comparison of Resampling Methods for Clustering Ensembles
-- Combination of multiple clusterings is an important task in the area of unsupervised learning. Inspired by the success of supervised bagging algorithms, we propose a resampling ...
Behrouz Minaei-Bidgoli, Alexander P. Topchy, Willi...
SIAMIS
2010
378views more  SIAMIS 2010»
15 years 28 days ago
Global Interactions in Random Field Models: A Potential Function Ensuring Connectedness
Markov random field (MRF) models, including conditional random field models, are popular in computer vision. However, in order to be computationally tractable, they are limited to ...
Sebastian Nowozin, Christoph H. Lampert
KDD
2004
ACM
132views Data Mining» more  KDD 2004»
16 years 6 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney