Greedy Criterion in Orthogonal Greedy Learning
نویسندگان
چکیده
منابع مشابه
Greedy metrics in orthogonal greedy learning
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. OGL then avoids the overfitting/u...
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ژورنال
عنوان ژورنال: IEEE Transactions on Cybernetics
سال: 2018
ISSN: 2168-2267,2168-2275
DOI: 10.1109/tcyb.2017.2669259