VibeMathedMath problems solved by AI

The Yun-Sra-Jadbabaie SS-RS-GD Inequalities

Yun, Sra and Jadbabaie posed as a COLT 2021 open question whether, for well-conditioned symmetric matrices, the operators encoding the expected iterate of single-shuffle SGD, random-reshuffle SGD and gradient descent on a quadratic finite sum satisfy WssWrsWgd\|W_{ss}\| \le \|W_{rs}\| \le \|W_{gd}\|. They do.

Result
Proved
Status
Resolved
AI contribution
AI-discovered
Method
Argument
Field
Optimization
Posed by
Chulhee Yun, Suvrit Sra, Ali Jadbabaie
Year posed
2021
Years open
5y
Solved
2026-06-16
Model
GPT-5.5 Pro (extended)
Vendor
OpenAI
Collaborators
Binghui Peng
Verification
Unreviewed
Publication
Preprint
Significance
15 / 100
Disclosed cost
Wikipedia
No dedicated article

What the AI did

The paper states the proof was found via GPT-5.5 Pro prompted by the author, and a footnote says the proof idea was completely generated by the model, linking the shared conversation. The write-up was assembled by the author.

Verification

Single-author arXiv preprint with the originating conversation linked; not yet peer-reviewed.

Source

arXiv:2607.22620 - A Resolution of the SS-RS-GD Inequalities

Discussion