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KDD
2010
ACM
265views Data Mining» more  KDD 2010»
15 years 6 months ago
Scalable influence maximization for prevalent viral marketing in large-scale social networks
Influence maximization, defined by Kempe, Kleinberg, and Tardos (2003), is the problem of finding a small set of seed nodes in a social network that maximizes the spread of influe...
Wei Chen, Chi Wang, Yajun Wang
TDP
2010
166views more  TDP 2010»
14 years 11 months ago
Communication-Efficient Privacy-Preserving Clustering
The ability to store vast quantities of data and the emergence of high speed networking have led to intense interest in distributed data mining. However, privacy concerns, as well ...
Geetha Jagannathan, Krishnan Pillaipakkamnatt, Reb...
DASFAA
2005
IEEE
141views Database» more  DASFAA 2005»
15 years 10 months ago
Learning Tree Augmented Naive Bayes for Ranking
Naive Bayes has been widely used in data mining as a simple and effective classification algorithm. Since its conditional independence assumption is rarely true, numerous algorit...
Liangxiao Jiang, Harry Zhang, Zhihua Cai, Jiang Su
CVPR
2007
IEEE
16 years 6 months ago
Element Rearrangement for Tensor-Based Subspace Learning
The success of tensor-based subspace learning depends heavily on reducing correlations along the column vectors of the mode-k flattened matrix. In this work, we study the problem ...
Shuicheng Yan, Dong Xu, Stephen Lin, Thomas S. Hua...
ICML
2005
IEEE
16 years 5 months ago
Supervised versus multiple instance learning: an empirical comparison
We empirically study the relationship between supervised and multiple instance (MI) learning. Algorithms to learn various concepts have been adapted to the MI representation. Howe...
Soumya Ray, Mark Craven