Differential Evolution Algorithm

Beyond the Gradient: Master Global Optimization with Differential Evolution If you have spent any time in the machine learning world, you are likely intimately familiar with Gradient Descent and its various turbo-charged derivatives (like Adam or RMSprop). Gradients are wonderful—assuming your optimization landscape is as smooth and predictable as a bowling green. But what happens when your loss landscape looks less like a gentle bowl and more like a jagged mountain range after an earthquake?