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» Selective Attention Improves Learning
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161
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GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
15 years 6 months ago
Informative sampling for large unbalanced data sets
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...
134
Voted
GECCO
2007
Springer
171views Optimization» more  GECCO 2007»
15 years 11 months ago
Toward a better understanding of rule initialisation and deletion
A number of heuristics have been used in Learning Classifier Systems to initialise parameters of new rules, to adjust fitness of parent rules when they generate offspring, and ...
Tim Kovacs, Larry Bull
ICC
2007
IEEE
15 years 11 months ago
A Measurement Based Dynamic Policy for Switched Processing Systems
Abstract- Switched Processing Systems (SPS) represent a canonical model for many areas of applications of communication, computer and manufacturing systems. They are characterized ...
Ying-Chao Hung, George Michailidis
MMM
2007
Springer
127views Multimedia» more  MMM 2007»
15 years 11 months ago
Optimizing the Throughput of Data-Driven Based Streaming in Heterogeneous Overlay Network
Recently, much attention has been paid on data-driven (or swarm-like) based live streaming systems due to its rapid growth in deployment over Internet. In such systems, nodes rando...
Meng Zhang, Chunxiao Chen, Yongqiang Xiong, Qian Z...
ICASSP
2010
IEEE
15 years 5 months ago
On the tracking performance of combinations of least mean squares and recursive least squares adaptive filters
Combinations of adaptive filters have attracted attention as a simple solution to improve filter performance, including tracking properties. In this paper, we consider combinati...
Vitor H. Nascimento, Magno T. M. Silva, Luis Anton...