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AAAI
2012
13 years 2 months ago
Semi-Supervised Kernel Matching for Domain Adaptation
In this paper, we propose a semi-supervised kernel matching method to address domain adaptation problems where the source distribution substantially differs from the target distri...
Min Xiao, Yuhong Guo
PAKDD
2007
ACM
110views Data Mining» more  PAKDD 2007»
15 years 5 months ago
Combining Convolution Kernels Defined on Heterogeneous Sub-structures
Convolution kernels, constructed by convolution of sub-kernels defined on sub-structures of composite objects, are widely used in classification, where one important issue is to ch...
Minlie Huang, Xiaoyan Zhu
ICML
2006
IEEE
16 years 15 days ago
Optimal kernel selection in Kernel Fisher discriminant analysis
In Kernel Fisher discriminant analysis (KFDA), we carry out Fisher linear discriminant analysis in a high dimensional feature space defined implicitly by a kernel. The performance...
Seung-Jean Kim, Alessandro Magnani, Stephen P. Boy...
JMLR
2012
13 years 2 months ago
Algorithms for Learning Kernels Based on Centered Alignment
This paper presents new and effective algorithms for learning kernels. In particular, as shown by our empirical results, these algorithms consistently outperform the so-called uni...
Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
COLT
2006
Springer
15 years 3 months ago
Mercer's Theorem, Feature Maps, and Smoothing
We study Mercer's theorem and feature maps for several positive definite kernels that are widely used in practice. The smoothing properties of these kernels will also be explo...
Ha Quang Minh, Partha Niyogi, Yuan Yao