Multilevel manifold learning with application to spectral clustering
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
A multilevel approach for nonnegative matrix factorization
Journal of Computational and Applied Mathematics
Parallel rare term vector replacement: Fast and effective dimensionality reduction for text
Journal of Parallel and Distributed Computing
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Dimension reduction techniques have been successfully applied to face recognition and text information retrieval. The process can be time-consuming when the data set is large. This paper presents a multilevel framework to reduce the size of the data set, prior to performing dimension reduction. The algorithm exploits nearest-neighbor graphs.It recursively coarsens the data by finding a maximal matching level by level.The coarsened data at the lowest level is then projected using a known linear dimensionality reduction method. The same linear mapping %as that of the lowest level is performed on the original data set, and on any new test data.The methods are illustrated on two applications: Eigenfaces (face recognition) and Latent Semantic Indexing (text mining). Experimental results indicate that the multilevel techniques proposed here %in this paper offer a very appealing cost to quality ratio.