论文标题
Adafamily：一个类似亚当的自适应梯度方法的家族
AdaFamily: A family of Adam-like adaptive gradient methods
论文作者
论文摘要
我们提出了Afafamily，这是一种训练深神经网络的新方法。它是一个自适应梯度方法的家族，可以解释为Adam，Andabelief和Adamomentum的优化算法的混合物。我们在标准数据集上进行图像分类的实验，证明我们所提出的方法的表现优于这些算法。
We propose AdaFamily, a novel method for training deep neural networks. It is a family of adaptive gradient methods and can be interpreted as sort of a blend of the optimization algorithms Adam, AdaBelief and AdaMomentum. We perform experiments on standard datasets for image classification, demonstrating that our proposed method outperforms these algorithms.
