Konstantinos E. Nikolakakis, Amin Karbasi, Dionysis Kalogerias
TL;DR本研究建立了优化算法，分析了批处理的优点，证明了基于批处理训练的渐进误差上下界。
Abstract
We establish matching upper and lower generalization error bounds for mini-batch gradient descent (GD) training with either deterministic or stochastic, data-independent, but otherwise arbitrary →