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BMCBI
2008
228views more  BMCBI 2008»
15 years 21 days ago
Adaptive diffusion kernel learning from biological networks for protein function prediction
Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
Liang Sun, Shuiwang Ji, Jieping Ye
105
Voted
JMLR
2008
116views more  JMLR 2008»
15 years 16 days ago
Support Vector Machinery for Infinite Ensemble Learning
Ensemble learning algorithms such as boosting can achieve better performance by averaging over the predictions of some base hypotheses. Nevertheless, most existing algorithms are ...
Hsuan-Tien Lin, Ling Li
115
Voted
TEC
2012
197views Formal Methods» more  TEC 2012»
13 years 3 months ago
Improving Generalization Performance in Co-Evolutionary Learning
Recently, the generalization framework in co-evolutionary learning has been theoretically formulated and demonstrated in the context of game-playing. Generalization performance of...
Siang Yew Chong, Peter Tino, Day Chyi Ku, Xin Yao
106
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ISCC
2006
IEEE
188views Communications» more  ISCC 2006»
15 years 6 months ago
Active Learning Driven Data Acquisition for Sensor Networks
Online monitoring of a physical phenomenon over a geographical area is a popular application of sensor networks. Networks representative of this class of applications are typicall...
Anish Muttreja, Anand Raghunathan, Srivaths Ravi, ...
113
Voted
IBPRIA
2009
Springer
15 years 5 months ago
Inference and Learning for Active Sensing, Experimental Design and Control
In this paper we argue that maximum expected utility is a suitable framework for modeling a broad range of decision problems arising in pattern recognition and related fields. Exa...
Hendrik Kück, Matthew Hoffman, Arnaud Doucet,...