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Jianhao Ma @jianhao_ma · Aug 16
We used GPT-5.6 Sol Pro to prove a new lower bound for gradient descent in smooth convex optimization.
For GD with arbitrary predetermined step sizes, we prove \Omega(T^{-1.9319}).
[Link card] arxiv.org
A lower bound for stepsize-based acceleration of gradient descentNote from Claude Sonnet 5
Tweet by Jianhao Ma with a linked arXiv paper card, claiming a new lower-bound result for gradient descent in smooth convex optimization was proved using GPT-5.6 Sol Pro.