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VLSID
2005
IEEE
105views VLSI» more  VLSID 2005»
15 years 4 months ago
Placement and Routing for 3D-FPGAs Using Reinforcement Learning and Support Vector Machines
The primary advantage of using 3D-FPGA over 2D-FPGA is that the vertical stacking of active layers reduce the Manhattan distance between the components in 3D-FPGA than when placed...
R. Manimegalai, E. Siva Soumya, V. Muralidharan, B...
SAC
2005
ACM
15 years 4 months ago
Stochastic scheduling of active support vector learning algorithms
Active learning is a generic approach to accelerate training of classifiers in order to achieve a higher accuracy with a small number of training examples. In the past, simple ac...
Gaurav Pandey, Himanshu Gupta, Pabitra Mitra
CSL
2006
Springer
14 years 11 months ago
Support vector machines for speaker and language recognition
Support vector machines (SVMs) have proven to be a powerful technique for pattern classification. SVMs map inputs into a high dimensional space and then separate classes with a hy...
William M. Campbell, Joseph P. Campbell, Douglas A...
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BMCBI
2006
201views more  BMCBI 2006»
14 years 11 months ago
Gene selection algorithms for microarray data based on least squares support vector machine
Background: In discriminant analysis of microarray data, usually a small number of samples are expressed by a large number of genes. It is not only difficult but also unnecessary ...
E. Ke Tang, Ponnuthurai N. Suganthan, Xin Yao
BMCBI
2007
153views more  BMCBI 2007»
14 years 11 months ago
A new pairwise kernel for biological network inference with support vector machines
Background: Much recent work in bioinformatics has focused on the inference of various types of biological networks, representing gene regulation, metabolic processes, protein-pro...
Jean-Philippe Vert, Jian Qiu, William Stafford Nob...