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ICRA
2009
IEEE
179views Robotics» more  ICRA 2009»
15 years 7 months ago
Automatic weight learning for multiple data sources when learning from demonstration
— Traditional approaches to programming robots are generally inaccessible to non-robotics-experts. A promising exception is the Learning from Demonstration paradigm. Here a polic...
Brenna Argall, Brett Browning, Manuela M. Veloso
WWW
2005
ACM
16 years 1 months ago
Thresher: automating the unwrapping of semantic content from the World Wide Web
We describe Thresher, a system that lets non-technical users teach their browsers how to extract semantic web content from HTML documents on the World Wide Web. Users specify exam...
Andrew Hogue, David R. Karger
ICA
2004
Springer
15 years 6 months ago
Source Separation on Astrophysical Data Sets from the WMAP Satellite
This paper presents and discusses the application of blind source separation to astrophysical data obtained with the WMAP satellite.
Guillaume Patanchon, Jacques Delabrouille, Jean-Fr...
105
Voted
DATAMINE
2006
130views more  DATAMINE 2006»
15 years 21 days ago
Mining Adaptive Ratio Rules from Distributed Data Sources
Different from traditional association-rule mining, a new paradigm called Ratio Rule (RR) was proposed recently. Ratio rules are aimed at capturing the quantitative association kno...
Jun Yan, Ning Liu, Qiang Yang, Benyu Zhang, QianSh...
164
Voted
AII
1992
15 years 4 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