Multiple Kernel Spectral Regression for Dimensionality Reduction
نویسندگان
چکیده
منابع مشابه
Spectral Regression for Dimensionality Reduction∗
Spectral methods have recently emerged as a powerful tool for dimensionality reduction and manifold learning. These methods use information contained in the eigenvectors of a data affinity (i.e., item-item similarity) matrix to reveal low dimensional structure in high dimensional data. The most popular manifold learning algorithms include Locally Linear Embedding, Isomap, and Laplacian Eigenmap...
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ژورنال
عنوان ژورنال: Journal of Applied Mathematics
سال: 2013
ISSN: 1110-757X,1687-0042
DOI: 10.1155/2013/427462