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» Differentially Private Approximation Algorithms
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KDD
2004
ACM
166views Data Mining» more  KDD 2004»
14 years 7 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
CCS
2006
ACM
13 years 11 months ago
Secure function evaluation with ordered binary decision diagrams
Privacy-preserving protocols allow multiple parties with private inputs to perform joint computation while preserving the privacy of their respective inputs. An important cryptogr...
Louis Kruger, Somesh Jha, Eu-Jin Goh, Dan Boneh
GLOBECOM
2009
IEEE
14 years 2 months ago
Sparse Decoding of Low Density Parity Check Codes Using Margin Propagation
—One of the key factors underlying the popularity of Low-density parity-check (LDPC) code is its iterative decoding algorithm that is amenable to efficient hardware implementati...
Ming Gu, Kiran Misra, Hayder Radha, Shantanu Chakr...
BMCBI
2007
197views more  BMCBI 2007»
13 years 7 months ago
Boolean networks using the chi-square test for inferring large-scale gene regulatory networks
Background: Boolean network (BN) modeling is a commonly used method for constructing gene regulatory networks from time series microarray data. However, its major drawback is that...
Haseong Kim, Jae K. Lee, Taesung Park
GIS
2009
ACM
14 years 8 months ago
Sea Floor Bathymetry Trackline Surface Fitting Without Visible Artifacts Using ODETLAP
High quality, artifact-free fitting a bathymetry (sea-floor) surface to very unevenly spaced depth data from ship tracklines is possible with ODETLAP (Overdetermined Laplacian Par...
Tsz-Yam Lau, W. Randolph Franklin, You Li, Zhongyi...