[esafak]

...because stochastic methods are implicit regularizers, leading to solutions that generalize better. Let's spell it out for those that don't know.

https://www.inference.vc/notes-on-the-origin-of-implicit-reg...

[jampekka]

OLS is a convex optimization problem, so this doesn't really apply. And for statistical analysis you really don't want to add poorly understood artificial noise to the parameter estimates anyway.

[esafak]

In general you do, because the unbiased estimates have higher generalization error. You are already dealing with sampling noise. I am not an expert in optimization, and what "poorly understood" means to you, but I know there is quite some research on the properties of SGD noise; e.g., https://francisbach.com/rethinking-sgd-noise/

Dissecting the Effects of SGD Noise in Distinct Regimes of Deep Learning https://arxiv.org/abs/2301.13703