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AII
1992
15 years 10 months ago
Learning from Multiple Sources of Inaccurate Data
Most theoretical models of inductive inference make the idealized assumption that the data available to a learner is from a single and accurate source. The subject of inaccuracies ...
Ganesh Baliga, Sanjay Jain, Arun Sharma
BMCBI
2010
154views more  BMCBI 2010»
15 years 6 months ago
An eScience-Bayes strategy for analyzing omics data
Background: The omics fields promise to revolutionize our understanding of biology and biomedicine. However, their potential is compromised by the challenge to analyze the huge da...
Martin Eklund, Ola Spjuth, Jarl E. S. Wikberg
ADC
2003
Springer
123views Database» more  ADC 2003»
15 years 12 months ago
A Distance-Based Packing Method for High Dimensional Data
Minkowski-sum cost model indicates that balanced data partitioning is not beneficial for high dimensional data. Thus we study several unbalanced partitioning methods and propose ...
Tae-wan Kim, Ki-Joune Li
ICDCS
2002
IEEE
15 years 11 months ago
A Fully Distributed Framework for Cost-Sensitive Data Mining
Data mining systems aim to discover patterns and extract useful information from facts recorded in databases. A widely adopted approach is to apply machine learning algorithms to ...
Wei Fan, Haixun Wang, Philip S. Yu, Salvatore J. S...
AAAI
1996
15 years 8 months ago
Learning Models for Multi-Source Integration
One issue involved in accessing multiple heterogeneous information sources is how to integrate the retrieved data. SIMS, an information mediator, handles this problem by mapping t...
Sheila Tejada, Craig A. Knoblock, Steven Minton