… the first moment rapidly, which is why it is referred to as rapidly adapting moment estimation
(… In this paper, we have proposed a new adaptive gradient method for training DNNs, which …

… Among all the variations and improvements, the adaptive moment estimation (Adam) is one
of the classics. However, Adam has also been pointed out to have non-convergence or error-…

… AT based on moment estimation (AT-ME) to address this problem. The proposed approach
uses moment estimation to serve as the algorithm of parameter estimation, which reduces the …

… , Adaptive Moment estimation method for Online AUC Maximization. It applies the estimation
of moments of … Our method mitigates the rapid decay of learning rates by using exponential …

… Additionally, we intend to verify if those that use adaptive moment estimation (such as Adam
and RMSProp) for parameter tuning have gains over others. Our motivation is to leverage …

… that combines an adaptive and momental bound algorithm with decoupled weight decay (AdaModW),
which has three-fold ideas: a) adopting an adaptive moment estimation (Adam) …

This paper considers adaptive estimation of regression models by means of generalized
method of moments estimators. Two models are considered, one with an iid disturbance that is …

… The rapid and high-precision harmonic detection and analysis technology will set the …
fast-converging adaptive parameter learning strategy using rectified adaptive moment estimation (…

… in treating the first moment estimate m and the second moment estimate v. Specifically, v …
where the loss landscape changes rapidly, the immediate responsiveness provided by g …

… unable to make investment decisions rapidly, especially in high-… moment estimation to
maintain the direction of the historical gradient and second-order moment estimation for adaptive …