Sparse ℓ1 and ℓ Center Classifiers
نویسندگان
چکیده
منابع مشابه
Bayesian Learning of Sparse Classifiers
Bayesian approaches to supervised learning use priors on the classifier parameters. However, few priors aim at achieving “sparse” classifiers, where irrelevant/redundant parameters are automatically set to zero. Two well-known ways of obtaining sparse classifiers are: use a zero-mean Laplacian prior on the parameters, and the “support vector machine” (SVM). Whether one uses a Laplacian prior or...
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ژورنال
عنوان ژورنال: IFAC-PapersOnLine
سال: 2020
ISSN: 2405-8963
DOI: 10.1016/j.ifacol.2020.12.322