arXiv Machine Learning By Yuxing Peng, Zhiqing Tang, Weijia Jia

The Cost of an Unknown Horizon for the Last Iterate of Clipped SGD under Heavy-Tailed Noise

Read the original on arXiv Machine Learning →

arXiv:2610. 33381v2 Announce Type: new Abstract: Training is often stopped at a data-dependent time, so guarantees for the last iterate must hold at all times simultaneously.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.