Hyperparameter tuning may have a fractal boundary, and someone built an interactive demo
S_Conradi · x · 2026-07-23
This post argues that hyperparameter tuning can literally behave like a fractal boundary.
The reasoning is that gradient descent is an iterated map, b8 b8 - b7
L(b8), which is mathematically similar to the recurrence that generates the Mandelbrot set. If you repeatedly apply a nonlinear update and ask whether the trajectory stays bounded, the stability boundary can become fractal. The author says they built an interactive version of the idea.
Related event: Research Shows Neural Network Learning Rate Boundaries are Fractal(4 posts)→
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