GPT-Assisted Proof Reveals Theoretical Limits of Gradient Descent Acceleration
prof_grimmer · x · 2026-08-12
A recent paper by Jianhao Ma and Yuxin Chen investigates the acceleration of gradient descent, with portions of the proof developed by GPT. The research proves that no gradient descent stepsize schedule can achieve full acceleration, specifically matching Nesterov's accelerated gradient method.
Previous work by Jason Altschuler and others had shown that a constant of p=1.2716 could be achieved. This new result establishes that the constant cannot exceed 1.9319, defining a tighter theoretical bound for the problem.
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