Luke Walters

KrADagrad: Kronecker approximation-domination gradient preconditioned stochastic optimization

Second order stochastic optimizers allow parameter update step size and direction to adapt to loss curvature, but have traditionally required too much memory and compute for deep learning. Recently, Shampoo [Gupta et al., 2018] introduced a Kronecker factored preconditioner to reduce these requireme…