Random Feature Maps via a Layered Random Projection (LaRP) Framework for Object Classification

4 Feb 2016A. G. ChungM. J. ShafieeA. Wong

The approximation of nonlinear kernels via linear feature maps has recently gained interest due to their applications in reducing the training and testing time of kernel-based learning algorithms. Current random projection methods avoid the curse of dimensionality by embedding the nonlinear feature space into a low dimensional Euclidean space to create nonlinear kernels... (read more)

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