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KDD
2009
ACM
227views Data Mining» more  KDD 2009»
14 years 9 months ago
Efficiently learning the accuracy of labeling sources for selective sampling
Many scalable data mining tasks rely on active learning to provide the most useful accurately labeled instances. However, what if there are multiple labeling sources (`oracles...
Pinar Donmez, Jaime G. Carbonell, Jeff Schneider
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
14 years 9 months ago
Multi-focal learning and its application to customer service support
In this study, we formalize a multi-focal learning problem, where training data are partitioned into several different focal groups and the prediction model will be learned within...
Yong Ge, Hui Xiong, Wenjun Zhou, Ramendra K. Sahoo...
KDD
2008
ACM
174views Data Mining» more  KDD 2008»
14 years 9 months ago
Effective label acquisition for collective classification
Information diffusion, viral marketing, and collective classification all attempt to model and exploit the relationships in a network to make inferences about the labels of nodes....
Mustafa Bilgic, Lise Getoor
KDD
2007
ACM
177views Data Mining» more  KDD 2007»
14 years 9 months ago
On-board analysis of uncalibrated data for a spacecraft at mars
Analyzing data on-board a spacecraft as it is collected enables several advanced spacecraft capabilities, such as prioritizing observations to make the best use of limited bandwid...
Benyang Tang, Kiri Wagstaff, Rebecca Castañ...
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
14 years 9 months ago
Local decomposition for rare class analysis
Given its importance, the problem of predicting rare classes in large-scale multi-labeled data sets has attracted great attentions in the literature. However, the rare-class probl...
Junjie Wu, Hui Xiong, Peng Wu, Jian Chen