Understanding deep learning (still) requires rethinking generalization
نویسندگان
چکیده
منابع مشابه
Understanding deep learning requires rethinking generalization
Despite their massive size, successful deep artificial neural networks can exhibit a remarkably small difference between training and test performance. Conventional wisdom attributes small generalization error either to properties of the model family, or to the regularization techniques used during training. Through extensive systematic experiments, we show how these traditional approaches fail...
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ژورنال
عنوان ژورنال: Communications of the ACM
سال: 2021
ISSN: 0001-0782,1557-7317
DOI: 10.1145/3446776