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» Selective Attention Improves Learning
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EUROS
2008
113views Robotics» more  EUROS 2008»
15 years 2 months ago
Measuring Motion Expressiveness in Wheeled Mobile Robots
This paper addresses the measurement of motion expressiveness in wheeled mobile robots. A neural network based supervised learning strategy is proposed as a method to fuse informat...
João Sequeira
110
Voted
JSA
2006
97views more  JSA 2006»
15 years 24 days ago
Dynamic feature selection for hardware prediction
It is often possible to greatly improve the performance of a hardware system via the use of predictive (speculative) techniques. For example, the performance of out-of-order micro...
Alan Fern, Robert Givan, Babak Falsafi, T. N. Vija...
129
Voted
BMCBI
2006
146views more  BMCBI 2006»
15 years 26 days ago
Recursive gene selection based on maximum margin criterion: a comparison with SVM-RFE
Background: In class prediction problems using microarray data, gene selection is essential to improve the prediction accuracy and to identify potential marker genes for a disease...
Satoshi Niijima, Satoru Kuhara
109
Voted
BMCBI
2007
217views more  BMCBI 2007»
15 years 25 days ago
On consensus biomarker selection
Background: Recent development of mass spectrometry technology enabled the analysis of complex peptide mixtures. A lot of effort is currently devoted to the identification of biom...
Janusz Dutkowski, Anna Gambin
BMCBI
2010
159views more  BMCBI 2010»
15 years 28 days ago
Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines
Background: Protein-protein interaction (PPI) plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods ha...
Alvaro J. González, Li Liao