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» Learning for control from multiple demonstrations
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ESANN
2006
14 years 11 months ago
Random Forests Feature Selection with K-PLS: Detecting Ischemia from Magnetocardiograms
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
Long Han, Mark J. Embrechts, Boleslaw K. Szymanski...
ESANN
2006
14 years 11 months ago
Margin based Active Learning for LVQ Networks
In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples during the model adaptation...
Frank-Michael Schleif, Barbara Hammer, Thomas Vill...
TPDS
2010
94views more  TPDS 2010»
14 years 8 months ago
MIMO Power Control for High-Density Servers in an Enclosure
—Power control is becoming a key challenge for effectively operating a modern data center. In addition to reducing operating costs, precisely controlling power consumption is an ...
Xiaorui Wang, Ming Chen, Xing Fu
CVPR
2006
IEEE
15 years 11 months ago
Image-Based Multiclass Boosting and Echocardiographic View Classification
We tackle the problem of automatically classifying cardiac view for an echocardiographic sequence as a multiclass object detection. As a solution, we present an imagebased multicl...
Shaohua Kevin Zhou, J. H. Park, Bogdan Georgescu, ...
ICDE
2005
IEEE
120views Database» more  ICDE 2005»
15 years 11 months ago
Corpus-based Schema Matching
Schema Matching is the problem of identifying corresponding elements in different schemas. Discovering these correspondences or matches is inherently difficult to automate. Past s...
Jayant Madhavan, Philip A. Bernstein, AnHai Doan, ...