Locally linear embedding

Kumar, R., Kulkarni, A., Jayaraman, V. K., Kulkarni, B. D. Strucmre-activity relationships using locally linear embedding assisted by support vector and lazy learning regressors. Internet Electron. J. Mol. Des. 2004, 3,... 

Sam T. Roweis and Lawrence K. Saul, Nonlinear dimensionality reduction by local linear embedding, Science, 290 (2000), 2323-2326. 

Des., 3,118-133 (2004). Structure-Activity Relationships Using Locally Linear Embedding Assisted by Support Vector and Lazy Learning Regressors. 

Roweis, S.T., Saul, L.K. Nonlinear dimensionality reduction by Locally Linear Embedding. Science 290, 2323-2326 (2000)... 

Kouropteva, O., Okun, O., Pietikainen, M. Selection of the optimal parameter value for the locally linear embedding algorithm. In Proceedings of the First International Conference on Fuzzy Systems and Knowledge Discovery, pp. 359-363 (2002)... 

Chang, H., Yeung, D.Y. Robust locally linear embedding. Ptittem Recognition 39,1053-1065... 

Perona, P., Polito, M. Grouping and dimensionality reduction by locally linear embedding. In Advances in Neural Information Processing Systems 14 Proceedings of the 2002 Conference... 

Donoho, D.L., Grimes, C. Hessian eigenmaps Locally linear embedding techniques for highdimensional data. Proceedings of the National Academy of Sciences of the United States of America (PNAS) 100(10), 5591-5596 (2003)... 

Unlike the global approaches previously described. Locally Linear Embedding (LLE) is a local approach and as described in Sect. 2.3.4 the x feature matrix is sparse. This sparse feature matrix is beneficial as it lowers the computational cost of the eigendecomposition. Specifically, the computational cost of eigendecomposition for a sparse nxn matrix, F, is 0 rn ) when using specific sparse analysis methods [8]. Here, r is the ratio of nonzero elements in F to the total number of elements n. 

Saul, L.K., Rowels, S. An introduction to locally linear embedding. URL http //www.es. toronto.edu/ roweis/lle/publications.html... 

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