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TSMC
2011
228views more  TSMC 2011»
14 years 11 months ago
Privacy-Preserving Outlier Detection Through Random Nonlinear Data Distortion
— Consider a scenario in which the data owner has some private/sensitive data and wants a data miner to access it for studying important patterns without revealing the sensitive ...
Kanishka Bhaduri, Mark D. Stefanski, Ashok N. Sriv...
KDD
2009
ACM
179views Data Mining» more  KDD 2009»
15 years 11 months ago
Identifying graphs from noisy and incomplete data
There is a growing wealth of data describing networks of various types, including social networks, physical networks such as transportation or communication networks, and biologic...
Galileo Mark S. Namata Jr., Lise Getoor
155
Voted
BMCBI
2007
160views more  BMCBI 2007»
15 years 4 months ago
Identifying protein complexes directly from high-throughput TAP data with Markov random fields
Background: Predicting protein complexes from experimental data remains a challenge due to limited resolution and stochastic errors of high-throughput methods. Current algorithms ...
Wasinee Rungsarityotin, Roland Krause, Arno Sch&ou...
DATAMINE
2006
164views more  DATAMINE 2006»
15 years 4 months ago
Fast Distributed Outlier Detection in Mixed-Attribute Data Sets
Efficiently detecting outliers or anomalies is an important problem in many areas of science, medicine and information technology. Applications range from data cleaning to clinica...
Matthew Eric Otey, Amol Ghoting, Srinivasan Partha...
136
Voted
BMCBI
2008
188views more  BMCBI 2008»
15 years 4 months ago
anNET: a tool for network-embedded thermodynamic analysis of quantitative metabolome data
Background: Compared to other omics techniques, quantitative metabolomics is still at its infancy. Complex sample preparation and analytical procedures render exact quantification...
Nicola Zamboni, Anne Kümmel, Matthias Heinema...