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» Entropy-based Adaptive Sampling
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FOCS
2010
IEEE
13 years 3 months ago
Boosting and Differential Privacy
Boosting is a general method for improving the accuracy of learning algorithms. We use boosting to construct improved privacy-preserving synopses of an input database. These are da...
Cynthia Dwork, Guy N. Rothblum, Salil P. Vadhan
BMCBI
2011
13 years 21 days ago
Statistical learning techniques applied to epidemiology: a simulated case-control comparison study with logistic regression
Background: When investigating covariate interactions and group associations with standard regression analyses, the relationship between the response variable and exposure may be ...
John J. Heine, Walker H. Land Jr., Kathleen M. Ega...
TWC
2010
13 years 14 days ago
Efficient Measurement Generation and Pervasive Sparsity for Compressive Data Gathering
We proposed compressive data gathering (CDG) that leverages compressive sampling (CS) principle to efficiently reduce communication cost and prolong network lifetime for large scal...
Chong Luo, Feng Wu, Jun Sun, Chang Wen Chen
ICASSP
2011
IEEE
12 years 9 months ago
Using the kernel trick in compressive sensing: Accurate signal recovery from fewer measurements
Compressive sensing accurately reconstructs a signal that is sparse in some basis from measurements, generally consisting of the signal’s inner products with Gaussian random vec...
Hanchao Qi, Shannon Hughes