We introduce Adam , an algorithm for rst-order gradient-based optimization of stochastic objective functions, based on adaptive estimates of lower-order mo- ments.

It is possible that Adam, being only nine generations ahead of Noah, with the time span of the Sudan Basin Polar Era covering 5,000 years, was not "the man" referred to in the creation, but …

Based on our proposed framework (AFM), we demonstrate that our proposed frame-work can be employed to analyze the convergence properties for a class of Adam-family methods with …

We consider a model where the data are generated as a combination of feature and noise patches, and analyze the convergence and generalization of Adam and GD for training a two …

Apr 29, 2025 · Gradient descent based optimization methods are the methods of choice to train deep neural networks in machine learning.

Weight decay is equally effective in both SGD and Adam. For SGD, it is equivalent to L2 regularization, while for Adam it is not. Optimal weight decay depends on the total number of …

Adam is a longtime champion of the environment and clean energy, as well as investments in infrastructure and mass transit. In Congress, Adam has led efforts to extend light rail and mass …