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» Learning from Multiple Sources of Inaccurate Data
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CEC
2010
IEEE
15 years 4 months ago
An adaptive ensemble of fuzzy ARTMAP neural networks for video-based face classification
A key feature in population based optimization algorithms is the ability to explore a search space and make a decision based on multiple solutions. In this paper, an incremental le...
Jean-François Connolly, Eric Granger, Rober...
158
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CCECE
2009
IEEE
15 years 10 months ago
Inverse data transformation for change detection in wind turbine diagnostics
A complex system is expected to show different nominal behaviors under different conditions, and the deviation over time from these nominal behaviors is an indicator of potential ...
Yanjun Yan, Lisa Ann Osadciw, Glen Benson, Eric Wh...
CHI
2006
ACM
16 years 3 months ago
Using hybrid networks for the analysis of online software development communities
Social network-based systems usually suffer from two major limitations: they tend to rely on a single data source (e.g. email traffic), and the form of network patterns is often p...
Yevgeniy Eugene Medynskiy, Nicolas Ducheneaut, Aym...
121
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KDD
2003
ACM
157views Data Mining» more  KDD 2003»
16 years 3 months ago
Cross-training: learning probabilistic mappings between topics
Classification is a well-established operation in text mining. Given a set of labels A and a set DA of training documents tagged with these labels, a classifier learns to assign l...
Sunita Sarawagi, Soumen Chakrabarti, Shantanu Godb...
ICRA
2009
IEEE
170views Robotics» more  ICRA 2009»
15 years 10 months ago
Imitation learning with generalized task descriptions
— In this paper, we present an approach that allows a robot to observe, generalize, and reproduce tasks observed from multiple demonstrations. Motion capture data is recorded in ...
Clemens Eppner, Jürgen Sturm, Maren Bennewitz...