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Vintage Factor Analysis with Varimax Performs Statistical Inference

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Karl Rohe: New paper! For the last century, we’ve misunderstood something fundamental about unsupervised learning. This paper fixes it. 🧵 https://arxiv.org/abs/2004.05387 https://t.co/7ReDLvedAP

13 replies, 941 likes


Karl Rohe: Varimax with PCA has so many secrets Muzhe Zeng (@muzheZ) and I found a big one in our recent paper In this thread, I want to describe some more varimax secrets that we use to analyze data in my lab https://twitter.com/karlrohe/status/1291132842601308164?s=20

3 replies, 145 likes


Peter Ralph: Use PCA? Check this out.

1 replies, 66 likes


Karl Rohe: We show how sparsity resolves the rotational invariance of factor analysis. It gets better. We show that PCA + Varimax estimates a huge class of "semi-parametric" models: SBMs, topic models, NMF, ICA, etc Filling seminar slots? I’d love zooming to you https://arxiv.org/abs/2004.05387 https://t.co/MoCo4bLoZX

9 replies, 56 likes


alex hayes: very cool new work from my lab!

3 replies, 48 likes


alex peysakhovich 🤖: This is awesome. Varimax (and other "interpretability maximizing" rotations) are such an important but underrated topic in modern ML.

0 replies, 20 likes


Dixie Leonard Appreciation Society: This is a really cool paper!

1 replies, 5 likes


Dr. Max Halupka 🏳️‍🌈: Ftw

0 replies, 2 likes


Karl Rohe: One of the biggest secrets of PCA is that if you have "radial streaks" in your components, then you should try rotating with varimax. here is a thread on a paper that describes this. https://twitter.com/karlrohe/status/1291132842601308164?s=20

1 replies, 0 likes


Content

Found on Aug 05 2020 at https://arxiv.org/pdf/2004.05387.pdf

PDF content of a computer science paper: Vintage Factor Analysis with Varimax Performs Statistical Inference