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ESWA
2007
127views more  ESWA 2007»
14 years 9 months ago
Clustering support vector machines for protein local structure prediction
Understanding the sequence-to-structure relationship is a central task in bioinformatics research. Adequate knowledge about this relationship can potentially improve accuracy for ...
Wei Zhong, Jieyue He, Robert W. Harrison, Phang C....
DCC
2009
IEEE
15 years 10 months ago
Compressed Kernel Perceptrons
Kernel machines are a popular class of machine learning algorithms that achieve state of the art accuracies on many real-life classification problems. Kernel perceptrons are among...
Slobodan Vucetic, Vladimir Coric, Zhuang Wang
ICDE
2004
IEEE
116views Database» more  ICDE 2004»
15 years 11 months ago
An Efficient Algorithm for Mining Frequent Sequences by a New Strategy without Support Counting
Mining sequential patterns in large databases is an important research topic. The main challenge of mining sequential patterns is the high processing cost due to the large amount ...
Ding-Ying Chiu, Yi-Hung Wu, Arbee L. P. Chen
VISSYM
2003
14 years 11 months ago
Improving Topological Segmentation of Three-dimensional Vector Fields
We present three enhancements to accelerate the extraction of separatrices of three-dimensional vector fields, using intelligently selected “sample” streamlines. These enhanc...
Karim Mahrous, Janine Bennett, Bernd Hamann, Kenne...
AGI
2008
14 years 11 months ago
Vector Symbolic Architectures: A New Building Material for Artificial General Intelligence
We provide an overview of Vector Symbolic Architectures (VSA), a class of structured associative memory models that offers a number of desirable features for artificial general int...
Simon D. Levy, Ross Gayler