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KDD
2010
ACM
265views Data Mining» more  KDD 2010»
9 years 5 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
KDD
2010
ACM
188views Data Mining» more  KDD 2010»
9 years 5 months ago
Inferring networks of diffusion and influence
Information diffusion and virus propagation are fundamental processes talking place in networks. While it is often possible to directly observe when nodes become infected, observi...
Manuel Gomez-Rodriguez, Jure Leskovec, Andreas Kra...
KDD
2010
ACM
228views Data Mining» more  KDD 2010»
9 years 5 months ago
Medical coding classification by leveraging inter-code relationships
Yan Yan, Glenn Fung, Jennifer G. Dy, Rómer ...
KDD
2010
ACM
222views Data Mining» more  KDD 2010»
9 years 5 months ago
Large linear classification when data cannot fit in memory
Recent advances in linear classification have shown that for applications such as document classification, the training can be extremely efficient. However, most of the existing t...
Hsiang-Fu Yu, Cho-Jui Hsieh, Kai-Wei Chang, Chih-J...
KDD
2010
ACM
242views Data Mining» more  KDD 2010»
9 years 5 months ago
A scalable two-stage approach for a class of dimensionality reduction techniques
Dimensionality reduction plays an important role in many data mining applications involving high-dimensional data. Many existing dimensionality reduction techniques can be formula...
Liang Sun, Betul Ceran, Jieping Ye
KDD
2010
ACM
245views Data Mining» more  KDD 2010»
9 years 5 months ago
Learning incoherent sparse and low-rank patterns from multiple tasks
We consider the problem of learning incoherent sparse and lowrank patterns from multiple tasks. Our approach is based on a linear multi-task learning formulation, in which the spa...
Jianhui Chen, Ji Liu, Jieping Ye
KDD
2010
ACM
161views Data Mining» more  KDD 2010»
9 years 5 months ago
Mass estimation and its applications
This paper introduces mass estimation—a base modelling mechanism in data mining. It provides the theoretical basis of mass and an efficient method to estimate mass. We show that...
Kai Ming Ting, Guang-Tong Zhou, Fei Tony Liu, Jame...
KDD
2010
ACM
247views Data Mining» more  KDD 2010»
9 years 5 months ago
Metric forensics: a multi-level approach for mining volatile graphs
Advances in data collection and storage capacity have made it increasingly possible to collect highly volatile graph data for analysis. Existing graph analysis techniques are not ...
Keith Henderson, Tina Eliassi-Rad, Christos Falout...
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