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AIR
2004
113views more  AIR 2004»
13 years 9 months ago
Class Noise vs. Attribute Noise: A Quantitative Study
Real-world data is never perfect and can often suffer from corruptions (noise) that may impact interpretations of the data, models created from the data and decisions made based on...
Xingquan Zhu, Xindong Wu
AI
2000
Springer
13 years 8 months ago
Wrapper induction: Efficiency and expressiveness
The Internet presents numerous sources of useful information--telephone directories, product catalogs, stock quotes, event listings, etc. Recently, many systems have been built th...
Nicholas Kushmerick
ML
2010
ACM
127views Machine Learning» more  ML 2010»
13 years 7 months ago
Stability and model selection in k-means clustering
Abstract Clustering Stability methods are a family of widely used model selection techniques for data clustering. Their unifying theme is that an appropriate model should result in...
Ohad Shamir, Naftali Tishby
FOCS
2010
IEEE
13 years 7 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
CORR
2010
Springer
185views Education» more  CORR 2010»
13 years 5 months ago
Analysing the behaviour of robot teams through relational sequential pattern mining
This report outlines the use of a relational representation in a Multi-Agent domain to model the behaviour of the whole system. A desired property in this systems is the ability of...
Grazia Bombini, Raquel Ros, Stefano Ferilli, Ramon...