jimmymvp t1_j806dx2 wrote on February 10, 2023 at 5:36 PM

Reply to comment by AdFew4357 in [D] Critique of statistics research from machine learning perspectives (and vice versa)? by fromnighttilldawn

Just communicating what I've heard. Nevertheless, I think the whole interpretable ML community (at the very least) would disagree with you on this one :). Reducing ML to "plug and chug" is well... Speaks for itself :D

AdFew4357 t1_j806plm wrote on February 10, 2023 at 5:38 PM

The whole landscape of ML research is a hunt to chase SOTA by tweaking an architecture here or using a different optimizer there and then squeezing out 0.2% accuracy on some well known imaging dataset in an attempt to churn out papers. That’s not science if you ask me.

jimmymvp t1_j83v503 wrote on February 11, 2023 at 1:16 PM

I'm not sure if you have a good overview of ML research if this is your claim. Sounds like you've read too many blog posts on transformers. I'd suggest going through some conference proceedings to get a good overview, there's some pretty rigorous (not just stats) stuff out there. I agree though that there is a substantial subset of research in ML that works towards tweaking and pushing the boundaries of what can be achieved with existing methods, which is for me personally exciting to see! A lot of cool stuff came out of scaling up and tweaking the architectures.