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COLT
1999
Springer
15 years 10 months ago
Covering Numbers for Support Vector Machines
—Support vector (SV) machines are linear classifiers that use the maximum margin hyperplane in a feature space defined by a kernel function. Until recently, the only bounds on th...
Ying Guo, Peter L. Bartlett, John Shawe-Taylor, Ro...
DASFAA
2004
IEEE
87views Database» more  DASFAA 2004»
15 years 9 months ago
UB-Tree Based Efficient Predicate Index with Dimension Transform for Pub/Sub System
For event filtering of publish/subscribe system, significant research efforts have been dedicated to techniques based on multiple one-dimensional indexes built on attributes of sub...
Botao Wang, Wang Zhang, Masaru Kitsuregawa
ECAL
2005
Springer
15 years 11 months ago
Biological Development of Cell Patterns: Characterizing the Space of Cell Chemistry Genetic Regulatory Networks
Abstract. Genetic regulatory networks (GRNs) control gene expression and are responsible for establishing the regular cellular patterns that constitute an organism. This paper intr...
Nicholas S. Flann, Jing Hu, Mayank Bansal, Vinay P...
ESWA
2007
127views more  ESWA 2007»
15 years 6 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....
183
Voted
PAMI
2010
132views more  PAMI 2010»
15 years 4 months ago
Maximum Likelihood Model Selection for 1-Norm Soft Margin SVMs with Multiple Parameters
—Adapting the hyperparameters of support vector machines (SVMs) is a challenging model selection problem, especially when flexible kernels are to be adapted and data are scarce....
Tobias Glasmachers, Christian Igel