On the Rate of Convergence of GD in Non-linear Neural Networks: An Adversarial Robustness Perspective

On the Rate of Convergence of GD in Non-linear Neural Networks: An Adversarial Robustness Perspective explores Develop algorithms to improve the convergence rate of Gradient Descent in non-linear neural networks for better adversarial robustness.. Commercial viability score: 2/10 in Optimization Algorithms.