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» Kernels for Semi-Structured Data
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ICML
2010
IEEE
13 years 11 months ago
COFFIN: A Computational Framework for Linear SVMs
In a variety of applications, kernel machines such as Support Vector Machines (SVMs) have been used with great success often delivering stateof-the-art results. Using the kernel t...
Sören Sonnenburg, Vojtech Franc
JAIR
2010
132views more  JAIR 2010»
13 years 8 months ago
Using Local Alignments for Relation Recognition
This paper discusses the problem of marrying structural similarity with semantic relatedness for Information Extraction from text. Aiming at accurate recognition of relations, we ...
Sophia Katrenko, Pieter W. Adriaans, Maarten van S...
ICDCS
2007
IEEE
14 years 4 months ago
Distributed Density Estimation Using Non-parametric Statistics
Learning the underlying model from distributed data is often useful for many distributed systems. In this paper, we study the problem of learning a non-parametric model from distr...
Yusuo Hu, Hua Chen, Jian-Guang Lou, Jiang Li
SIGKDD
2000
139views more  SIGKDD 2000»
13 years 9 months ago
Support Vector Machines: Hype or Hallelujah?
Support Vector Machines (SVMs) and related kernel methods have become increasingly popular tools for data mining tasks such as classification, regression, and novelty detection. T...
Kristin P. Bennett, Colin Campbell
ECCV
2006
Springer
14 years 12 months ago
Extending Kernel Fisher Discriminant Analysis with the Weighted Pairwise Chernoff Criterion
Many linear discriminant analysis (LDA) and kernel Fisher discriminant analysis (KFD) methods are based on the restrictive assumption that the data are homoscedastic. In this paper...
Guang Dai, Dit-Yan Yeung, Hong Chang