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131
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JMLR
2010
162views more  JMLR 2010»
14 years 7 months ago
A Surrogate Modeling and Adaptive Sampling Toolbox for Computer Based Design
An exceedingly large number of scientific and engineering fields are confronted with the need for computer simulations to study complex, real world phenomena or solve challenging ...
Dirk Gorissen, Ivo Couckuyt, Piet Demeester, Tom D...
DBSEC
2007
89views Database» more  DBSEC 2007»
15 years 2 months ago
Design and Analysis of Querying Encrypted Data in Relational Databases
Security and privacy concerns as well as legal considerations force many companies to encrypt the sensitive data in databases. However, storing the data in an encrypted format enta...
Mustafa Canim, Murat Kantarcioglu
114
Voted
KDD
2009
ACM
227views Data Mining» more  KDD 2009»
16 years 1 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
NN
2008
Springer
143views Neural Networks» more  NN 2008»
15 years 15 days ago
A batch ensemble approach to active learning with model selection
Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...
Masashi Sugiyama, Neil Rubens
126
Voted
KDD
2012
ACM
178views Data Mining» more  KDD 2012»
13 years 3 months ago
Mining emerging patterns by streaming feature selection
Building an accurate emerging pattern classifier with a highdimensional dataset is a challenging issue. The problem becomes even more difficult if the whole feature space is unava...
Kui Yu, Wei Ding 0003, Dan A. Simovici, Xindong Wu