A. Engelbrecht

Oscillation-Aware Deep Learning Optimization Using Second-Order Velocity Derivatives

Gradient-based optimization methods are fundamental to deep learning but often suffer from oscillatory behavior, slow convergence, and instability in non-convex loss landscapes. This paper introduces an oscillation-aware optimization framework based on second-order velocity derivatives, referred to as the second-order...