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» Efficient Sensor Selection for Active Information Fusion
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INFOCOM
2007
IEEE
14 years 4 months ago
Randomized k-Coverage Algorithms For Dense Sensor Networks
— We propose new algorithms to achieve k-coverage in dense sensor networks. In such networks, covering sensor locations approximates covering the whole area. However, it has been...
Mohamed Hefeeda, M. Bagheri
COLING
2010
13 years 5 months ago
A Comparison of Models for Cost-Sensitive Active Learning
Active Learning (AL) is a selective sampling strategy which has been shown to be particularly cost-efficient by drastically reducing the amount of training data to be manually ann...
Katrin Tomanek, Udo Hahn
WWW
2006
ACM
14 years 10 months ago
Large-scale text categorization by batch mode active learning
Large-scale text categorization is an important research topic for Web data mining. One of the challenges in large-scale text categorization is how to reduce the amount of human e...
Steven C. H. Hoi, Rong Jin, Michael R. Lyu
BMCBI
2010
182views more  BMCBI 2010»
13 years 10 months ago
L2-norm multiple kernel learning and its application to biomedical data fusion
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
Shi Yu, Tillmann Falck, Anneleen Daemen, Lé...
IROS
2006
IEEE
217views Robotics» more  IROS 2006»
14 years 4 months ago
Active SLAM using Model Predictive Control and Attractor based Exploration
– Active SLAM poses the challenge for an autonomous robot to plan efficient paths simultaneous to the SLAM process. The uncertainties of the robot, map and sensor measurements, a...
Cindy Leung, Shoudong Huang, Gamini Dissanayake