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132
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ICANN
2005
Springer
15 years 6 months ago
The LCCP for Optimizing Kernel Parameters for SVM
Abstract. Tuning hyper-parameters is a necessary step to improve learning algorithm performances. For Support Vector Machine classifiers, adjusting kernel parameters increases dra...
Sabri Boughorbel, Jean-Philippe Tarel, Nozha Bouje...
ICNP
2007
IEEE
15 years 7 months ago
HEXA: Compact Data Structures for Faster Packet Processing
—Data structures representing directed graphs with edges labeled by symbols from a finite alphabet are used to implement packet processing algorithms used in a variety of network...
Sailesh Kumar, Jonathan S. Turner, Patrick Crowley...
105
Voted
JCIT
2008
165views more  JCIT 2008»
15 years 18 days ago
Mining Processes using cluster approach for representing workflows
Although much attention is being paid to business Intelligence during the past decades, the design for applying business Intelligence and particularly in a workflow processes is s...
N. P. Kavya, M. V. Sathyanarayana, N. C. Naveen
94
Voted
ICML
2004
IEEE
16 years 1 months ago
Improving SVM accuracy by training on auxiliary data sources
The standard model of supervised learning assumes that training and test data are drawn from the same underlying distribution. This paper explores an application in which a second...
Pengcheng Wu, Thomas G. Dietterich
UM
2007
Springer
15 years 6 months ago
Evaluating a Simulated Student Using Real Students Data for Training and Testing
: SimStudent is a machine-learning agent that learns cognitive skills by demonstration. It was originally developed as a building block of the Cognitive Tutor Authoring Tools (CTAT...
Noboru Matsuda, William W. Cohen, Jonathan Sewall,...