Gorkem Yilmaz

A cross-domain empirical benchmark of quantum-inspired and classical optimization algorithms for machine learning

Quantum-inspired (QI) optimizers are increasingly proposed as alternatives to classical gradient-based training, yet are frequently benchmarked through classical stand-ins rather than themselves. Across tabular, vision, and language tasks we evaluate three classes: direct implementations of published update rules (Spal...