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KDD
2007
ACM
159views Data Mining» more  KDD 2007»
15 years 10 months ago
Constraint-driven clustering
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Rong Ge, Martin Ester, Wen Jin, Ian Davidson
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
15 years 10 months ago
Unsupervised learning on k-partite graphs
Various data mining applications involve data objects of multiple types that are related to each other, which can be naturally formulated as a k-partite graph. However, the resear...
Bo Long, Xiaoyun Wu, Zhongfei (Mark) Zhang, Philip...
STOC
2007
ACM
140views Algorithms» more  STOC 2007»
15 years 10 months ago
On the submodularity of influence in social networks
We prove and extend a conjecture of Kempe, Kleinberg, and Tardos (KKT) on the spread of influence in social networks. A social network can be represented by a directed graph where...
Elchanan Mossel, Sébastien Roch
STOC
2005
ACM
135views Algorithms» more  STOC 2005»
15 years 10 months ago
On the bias of traceroute sampling: or, power-law degree distributions in regular graphs
Understanding the graph structure of the Internet is a crucial step for building accurate network models and designing efficient algorithms for Internet applications. Yet, obtaini...
Dimitris Achlioptas, Aaron Clauset, David Kempe, C...
STOC
2005
ACM
129views Algorithms» more  STOC 2005»
15 years 10 months ago
Learning with attribute costs
We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...
Haim Kaplan, Eyal Kushilevitz, Yishay Mansour
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