154 search results - page 12 / 31 » Incremental Nonlinear Dimensionality Reduction by Manifold L... |
PAKDD
2005
ACM
15 years 5 months ago
2005
ACM
We propose adaptive nonlinear auto-associative modeling (ANAM) based on Locally Linear Embedding algorithm (LLE) for learning intrinsic principal features of each concept separatel...
117
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NIPS
2001
15 years 1 months ago
2001
Drawing on the correspondence between the graph Laplacian, the Laplace-Beltrami operator on a manifold, and the connections to the heat equation, we propose a geometrically motiva...
98
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PAKDD
2010
ACM
14 years 9 months ago
2010
ACM
Data mining tasks results are usually improved by reducing the dimensionality of data. This improvement however is achieved harder in the case that data lay on a non linear manifol...
104
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ICIP
2005
IEEE
16 years 1 months ago
2005
IEEE
We study the use of kernel subspace methods that learn low-dimensional subspace representations for classification tasks. In particular, we propose a new method called kernel weigh...
95
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ICMCS
2005
IEEE
15 years 5 months ago
2005
IEEE
Semi-definite Embedding (SDE) has been a recently proposed to maximize the sum of pair wise squared distances between outputs while the input data and outputs are locally isometri...