me trying to cut my ICML rebuttal down to <5000 characters

If people knew how much of my PhD has consisted of reading about something new, referencing back to Elements of Statistical Learning, and simply writing down what I learned… It feels like a cheat code!

Alicia Curth@aliciacurth.bsky.social · 2y ago

btw this is why friends dont let friends skip the “boring classical ML” chapters in Elements of Statistical Learning‼️ (True story: the origin of this case study is that @alanjeffares.bsky.social[big EoSL nerd] looked at the neural net eq&said “kinda looks like GBTs in EoSL Ch10”&we went from there)

Part 2: Why do boosted trees outperform deep learning on tabular data?? @alanjeffares.bsky.social & I suspected that answers to this are obfuscated by the 2 being considered very different algs🤔 Instead we show they are more similar than you’d think — making their diffs smaller but predictive!🧵1/n

i’m too lazy to make a thinly-veiled self-promotion “starter pack”, so if you could all add me anyway that would be great…

From double descent to grokking, deep learning sometimes works in unpredictable ways.. or does it? For NeurIPS(my final PhD paper!), @alanjeffares.bsky.social & I explored if&how smart linearisation can help us better understand&predict numerous odd deep learning phenomena — and learned a lot..🧵1/n

and all of a sudden, my feed changed from musk and outrage to matrices and optimisers…