incorporate feedback into our final revision. 4 [R1]: " I don't exactly see if small batch vs large batch captures this phenomenon; if yes should say explicitly. "
–Neural Information Processing Systems
We thank the reviewers for the detailed and insightful reviews. As the reviews noted, our work 1) introduces "novel Smith et al. [2017] make an explicit connection between small vs. large batch "A small discussion on if the phenomenon has been observed for different datasets/tasks with different optimizers" The phenomenon may not be true for other optimizers such as Adam, though. "concept of "memorizable and generalizable", though intuitive, is sketchy and not formally explained ... authors We acknowledge that the terms "memorizable" and "generalizable" are potentially confusing. We will revise our terminology to clarify this distinction. By "inherently noisy", we refer to the fact that high noise in the datapoints will necessitate larger sample complexity.
Neural Information Processing Systems
Aug-20-2025, 00:46:19 GMT
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