1 citations · 1 across the 3 of their papers we have counts for
3 papers
Compute-Optimal LLMs Provably Generalize Better With Scale
Marc Finzi, Sanyam Kapoor, Diego Granziol +4
Why do larger language models generalize better? To investigate this question, we develop generalization bounds on the pretraining objective of large language models (LLMs) in the…
Searching for Efficient Linear Layers over a Continuous Space of Structured Matrices
Andres Potapczynski, Shikai Qiu, Marc Finzi +6
Dense linear layers are the dominant computational bottleneck in large neural networks, presenting a critical need for more efficient alternatives. Previous efforts focused on a sm…
Riemannian Residual Neural Networks
Isay Katsman, Eric Ming Chen, Sidhanth Holalkere +4
Recent methods in geometric deep learning have introduced various neural networks to operate over data that lie on Riemannian manifolds. Such networks are often necessary to learn…