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» Prediction on Spike Data Using Kernel Algorithms
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MINENET
2006
ACM
15 years 3 months ago
SVM learning of IP address structure for latency prediction
We examine the ability to exploit the hierarchical structure of Internet addresses in order to endow network agents with predictive capabilities. Specifically, we consider Suppor...
Robert Beverly, Karen R. Sollins, Arthur Berger
CDES
2006
118views Hardware» more  CDES 2006»
14 years 11 months ago
Improving the System Performance by a Dynamic File Prediction Model
As the speed gap between CPU and I/O is getting wider and wider, I/O latency plays a more important role to the overall system performance than it used to be. Prefetching consecut...
Tsozen Yeh, Joseph Arul, Kuo-Hsin Tien, I-Fan Chen...
ICCV
2005
IEEE
15 years 3 months ago
Fast Global Kernel Density Mode Seeking with Application to Localisation and Tracking
We address the problem of seeking the global mode of a density function using the mean shift algorithm. Mean shift, like other gradient ascent optimisation methods, is susceptible...
Chunhua Shen, Michael J. Brooks, Anton van den Hen...
BMCBI
2006
99views more  BMCBI 2006»
14 years 9 months ago
Genetic algorithm learning as a robust approach to RNA editing site prediction
Background: RNA editing is one of several post-transcriptional modifications that may contribute to organismal complexity in the face of limited gene complement in a genome. One f...
James Thompson, Shuba Gopal
PR
2008
129views more  PR 2008»
14 years 9 months ago
A comparison of generalized linear discriminant analysis algorithms
7 Linear discriminant analysis (LDA) is a dimension reduction method which finds an optimal linear transformation that maximizes the class separability. However, in undersampled p...
Cheong Hee Park, Haesun Park