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Nonlinear Representation and Dimensionality Reduction

2023
Hye Sun Yun   +3 more
openaire   +1 more source

Nonlinear Dimensionality Reduction and Manifold Learning

2013
We have little visual guidance to help us identify any meaningful lowdimensional structure hidden in high-dimensional data. The linear projection methods of Chapter 7 can be extremely useful in discovering lowdimensional structure when the data actually lie in a linear (or approximately linear) lower-dimensional subspace (called a manifold) ℳ of input ...
openaire   +1 more source

Nonlinear Dimensionality Reduction for Data with Disconnected Neighborhood Graph

Neural Processing Letters, 2017
Jicong Fan, T. Chow, Mingbo Zhao, J. Ho
semanticscholar   +1 more source

Nonlinear Methods for Dimensionality Reduction

2013
Charles K. Chui, Jianzhong Wang
openaire   +1 more source

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