Beyond the Markovian Assumption: Robust Optimization via Fractional Weyl Integrals in Imbalanced Data

ArXi:2603.08377v1 Announce Type: new Standard Gradient Descent and its modern variants assume local, Markovian weight updates, making them highly susceptible to noise and overfitting. This limitation becomes critically severe in extremely imbalanced datasets such as financial fraud detection where dominant class gradients systematically overwrite the subtle signals of the minority class. In this paper, we