Greedy metrics in orthogonal greedy learning

13 Nov 2014 Lin Xu Shaobo Lin Jinshan Zeng Zongben Xu

Orthogonal greedy learning (OGL) is a stepwise learning scheme that adds a new atom from a dictionary via the steepest gradient descent and build the estimator via orthogonal projecting the target function to the space spanned by the selected atoms in each greedy step. Here, "greed" means choosing a new atom according to the steepest gradient descent principle... (read more)

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