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» Differentially Private Approximation Algorithms
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FOCS
2010
IEEE
13 years 5 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
COLT
1999
Springer
13 years 12 months ago
An Adaptive Version of the Boost by Majority Algorithm
We propose a new boosting algorithm. This boosting algorithm is an adaptive version of the boost by majority algorithm and combines bounded goals of the boost by majority algorith...
Yoav Freund
SIP
2003
13 years 9 months ago
Design of Full Band IIR Digital Differentiators
This paper presents an efficient method for designing full band IIR digital differentiators in the complex Chebyshev sense. The proposed method is based on the formulation of a g...
Xi Zhang, Toshinori Yoshikawa
SIGMOD
2011
ACM
283views Database» more  SIGMOD 2011»
12 years 10 months ago
iReduct: differential privacy with reduced relative errors
Prior work in differential privacy has produced techniques for answering aggregate queries over sensitive data in a privacypreserving way. These techniques achieve privacy by addi...
Xiaokui Xiao, Gabriel Bender, Michael Hay, Johanne...
TOMS
2008
87views more  TOMS 2008»
13 years 7 months ago
Efficient Contouring on Unstructured Meshes for Partial Differential Equations
We introduce three fast contouring algorithms for visualizing the solution of Partial Differential Equations based on the PCI (Pure Cubic Interpolant). The PCI is a particular pie...
Hassan Goldani-Moghaddam, Wayne H. Enright