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cs.LG2021★ 1 cited
Minimization of Stochastic First-order Oracle Complexity of Adaptive Methods for Nonconvex Optimization
Hideaki Iiduka
Numerical evaluations have definitively shown that, for deep learning optimizers such as stochastic gradient descent, momentum, and adaptive methods, the number of steps needed to…
math.OC2021
The Number of Steps Needed for Nonconvex Optimization of a Deep Learning Optimizer is a Rational Function of Batch Size
Hideaki Iiduka
Recently, convergence as well as convergence rate analyses of deep learning optimizers for nonconvex optimization have been widely studied. Meanwhile, numerical evaluations for the…