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» Fisher Kernels for Relational Data
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210
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BMCBI
2008
159views more  BMCBI 2008»
15 years 6 months ago
Estimation and testing for the effect of a genetic pathway on a disease outcome using logistic kernel machine regression via log
Background: Growing interest on biological pathways has called for new statistical methods for modeling and testing a genetic pathway effect on a health outcome. The fact that gen...
Dawei Liu, Debashis Ghosh, Xihong Lin
177
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KDD
2009
ACM
230views Data Mining» more  KDD 2009»
16 years 6 months ago
Cross domain distribution adaptation via kernel mapping
When labeled examples are limited and difficult to obtain, transfer learning employs knowledge from a source domain to improve learning accuracy in the target domain. However, the...
ErHeng Zhong, Wei Fan, Jing Peng, Kun Zhang, Jiang...
JMLR
2011
148views more  JMLR 2011»
15 years 1 months ago
Bayesian Generalized Kernel Mixed Models
We propose a fully Bayesian methodology for generalized kernel mixed models (GKMMs), which are extensions of generalized linear mixed models in the feature space induced by a repr...
Zhihua Zhang, Guang Dai, Michael I. Jordan
185
Voted
ICFCA
2009
Springer
15 years 3 months ago
A Concept Lattice-Based Kernel for SVM Text Classification
Abstract. Standard Support Vector Machines (SVM) text classification relies on bag-of-words kernel to express the similarity between documents. We show that a document lattice can ...
Claudio Carpineto, Carla Michini, Raffaele Nicolus...
ICML
2004
IEEE
16 years 7 months ago
K-means clustering via principal component analysis
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
Chris H. Q. Ding, Xiaofeng He