Our results concisely explain the interplay between the learning rate, the noise variance in the gradient oracle, and the strength ofthetime drift. The high-probability results merely assume that thegradient noise and time drift have light tails. Moreover, none of the results require the objectives to have bounded domains.

Our results concisely explain the interplay between the learning rate, the noise variance in the gradient oracle, and the strength ofthetime drift. The high-probability results merely assume that thegradient noise and time drift have light tails. Moreover, none of the results require the objectives to have bounded domains.

Despite the extensive application of multi-pass SGD in practice, there are only a few theoretical techniques being developed to study the generalization of multi-pass SGD.

Despite the extensive application of multi-pass SGD in practice, there are only a few theoretical techniques being developed to study the generalization of multi-pass SGD.

Consequently, detecting whether a text is generated by LLMs has become increasingly important.

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