GPT-5.6 used to prove new gradient descent lower bound
PMinervini · x · 2026-08-17
Retweets a research summary stating that GPT-5.6 Sol Pro was used to prove a new lower bound for gradient descent in smooth convex optimization. The proof establishes a lower bound of Ω(T^-1.9319) for GD with arbitrary predetermined step sizes.
Related event: GPT-5.6 Helps Prove New Lower Bound for Gradient Descent(2 posts)→
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