madgrad: madgrad

In sjSDM: Scalable Joint Species Distribution Modeling

madgrad

Description

stochastic gradient descent optimizer

Usage

madgrad(momentum = 0.9, weight_decay = 0, eps = 1e-06)

Arguments

momentum	strength of momentum
weight_decay	l2 penalty on weights
eps	epsilon

Value

Anonymous function that returns optimizer when called.

References

Defazio, A., & Jelassi, S. (2021). Adaptivity without Compromise: A Momentumized, Adaptive, Dual Averaged Gradient Method for Stochastic Optimization. arXiv preprint arXiv:2101.11075.

sjSDM documentation built on Nov. 5, 2025, 7:10 p.m.