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ICML
2004
IEEE
14 years 24 days ago
Learning a kernel matrix for nonlinear dimensionality reduction
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul
ML
2006
ACM
121views Machine Learning» more  ML 2006»
13 years 7 months ago
Model-based transductive learning of the kernel matrix
This paper addresses the problem of transductive learning of the kernel matrix from a probabilistic perspective. We define the kernel matrix as a Wishart process prior and construc...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
KDD
2005
ACM
143views Data Mining» more  KDD 2005»
14 years 7 months ago
SVM selective sampling for ranking with application to data retrieval
Learning ranking (or preference) functions has been a major issue in the machine learning community and has produced many applications in information retrieval. SVMs (Support Vect...
Hwanjo Yu