IAdaPID-ADG integrates non-increasing effective learning rates from AMSGrad and gradient-difference modulation from DiffGrad into AdaPID, yielding better convergence and stability than prior optimizers on MNIST, CIFAR10, IARC, and AnnoCerv.
A method for unconstrained convex minimization problem with the rate of convergence o (1/kˆ 2)
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An Improved Adaptive PID Optimizer with Enhanced Convergence and Stability for Deep Learning
IAdaPID-ADG integrates non-increasing effective learning rates from AMSGrad and gradient-difference modulation from DiffGrad into AdaPID, yielding better convergence and stability than prior optimizers on MNIST, CIFAR10, IARC, and AnnoCerv.