MADGRAD

2000년 도입 · 논문 1편에서 사용

The MADGRAD method contains a series of modifications to the AdaGrad-DA method to improve its performance on deep learning optimization problems. It gives state-of-the-art generalization performance across a diverse set of problems, including those that Adam normally under-performs on.

출처: Adaptivity without Compromise: A Momentumized, Adaptive, Dual Averaged Gradient Method for Stochastic Optimization

소개 논문: Adaptivity without Compromise: A Momentumized, Adaptive, Dual Averaged Gradient Method for Stochastic Optimization