Machine Learning
Nonlinear component analysis as a kernel eigenvalue problem
Neural Computation
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Training Support Vector Machines: an Application to Face Detection
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Privacy-preserving collaborative data mining
Privacy-preserving collaborative data mining
Differentially Private Empirical Risk Minimization
The Journal of Machine Learning Research
A near-optimal algorithm for differentially-private principal components
The Journal of Machine Learning Research
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Privacy is an important issue in the collaborative data mining since privacy concerns may prevent the parties from directly sharing the data and some types of information about the data. How multiple parties collaboratively conduct data mining without breaching data privacy presents a challenge. This paper seeks to investigate solutions for privacy-preserving support vector machine classification which is one of data mining tasks. The goal is to obtain accurate classification results without disclosing private data.