随机梯度下降式放松相当于在离散优化和推理问题中的大都会动态

Maria Chiara Angelini1,2, Angelo Giorgio Cavaliere3, Raffaele Marino4

  • 1Dipartimento di Fisica, Sapienza Università di Roma, P.le Aldo Moro 5, 00185, Rome, Italy. maria.chiara.angelini@roma1.infn.it.

Scientific reports
|May 21, 2024
PubMed
概括

随机梯度下降 (SGD) 在离散优化中密切反映了大都市蒙特卡洛的动态. 这种等价性有助于优化SGD迷你批量大小,以提高机器学习推理问题的性能.

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