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IJCNN
2007
IEEE
14 years 2 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
BMCBI
2008
130views more  BMCBI 2008»
13 years 8 months ago
Function approximation approach to the inference of reduced NGnet models of genetic networks
Background: The inference of a genetic network is a problem in which mutual interactions among genes are deduced using time-series of gene expression patterns. While a number of m...
Shuhei Kimura, Katsuki Sonoda, Soichiro Yamane, Hi...
SIGCOMM
2009
ACM
14 years 2 months ago
A programmable, generic forwarding element approach for dynamic network functionality
Communication networks are growing exponentially, and new services and applications are being introduced unceasingly. To meet the demands of these services and applications, curre...
Ran Giladi, Niv Yemini
MICRO
2006
IEEE
127views Hardware» more  MICRO 2006»
14 years 1 months ago
A Predictive Performance Model for Superscalar Processors
Designing and optimizing high performance microprocessors is an increasingly difficult task due to the size and complexity of the processor design space, high cost of detailed si...
P. J. Joseph, Kapil Vaswani, Matthew J. Thazhuthav...
TNN
2010
168views Management» more  TNN 2010»
13 years 2 months ago
On the selection of weight decay parameter for faulty networks
The weight-decay technique is an effective approach to handle overfitting and weight fault. For fault-free networks, without an appropriate value of decay parameter, the trained ne...
Andrew Chi-Sing Leung, Hongjiang Wang, John Sum