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» A Fully Distributed Framework for Cost-Sensitive Data Mining
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KDD
2006
ACM
173views Data Mining» more  KDD 2006»
14 years 8 months ago
Robust information-theoretic clustering
How do we find a natural clustering of a real world point set, which contains an unknown number of clusters with different shapes, and which may be contaminated by noise? Most clu...
Christian Böhm, Christos Faloutsos, Claudia P...
KDD
2008
ACM
213views Data Mining» more  KDD 2008»
14 years 8 months ago
Heterogeneous data fusion for alzheimer's disease study
Effective diagnosis of Alzheimer's disease (AD) is of primary importance in biomedical research. Recent studies have demonstrated that neuroimaging parameters are sensitive a...
Jieping Ye, Kewei Chen, Teresa Wu, Jing Li, Zheng ...
ICAI
2004
13 years 9 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...
SDM
2012
SIAM
282views Data Mining» more  SDM 2012»
11 years 10 months ago
Citation Prediction in Heterogeneous Bibliographic Networks
To reveal information hiding in link space of bibliographical networks, link analysis has been studied from different perspectives in recent years. In this paper, we address a no...
Xiao Yu, Quanquan Gu, Mianwei Zhou, Jiawei Han
SIGMOD
2012
ACM
220views Database» more  SIGMOD 2012»
11 years 10 months ago
GUPT: privacy preserving data analysis made easy
It is often highly valuable for organizations to have their data analyzed by external agents. However, any program that computes on potentially sensitive data risks leaking inform...
Prashanth Mohan, Abhradeep Thakurta, Elaine Shi, D...