Why random reshuffling beats stochastic gradient descent
نویسندگان
چکیده
منابع مشابه
Stochastic Learning under Random Reshuffling
In empirical risk optimization, it has been observed that stochastic gradient implementations that rely on random reshuffling of the data achieve better performance than implementations that rely on sampling the data uniformly. Recent works have pursued justifications for this behavior by examining the convergence rate of the learning process under diminishing step-sizes. This work focuses on t...
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ژورنال
عنوان ژورنال: Mathematical Programming
سال: 2019
ISSN: 0025-5610,1436-4646
DOI: 10.1007/s10107-019-01440-w