"Understanding Scaling Laws with Statistical and Approximation Theory for ..."

Alexander Havrilla, Wenjing Liao (2024)

> Home

Details and statistics

DOI: —

access: open

type: Conference or Workshop Paper

metadata version: 2025-02-13

- view
  - electronic edition @ nips.cc (open access)
- export record
  dblp key:
  - conf/nips/HavrillaL24
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/conf/nips/HavrillaL24
Alexander Havrilla, Wenjing Liao:
Understanding Scaling Laws with Statistical and Approximation Theory for Transformer Neural Networks on Intrinsically Low-dimensional Data. NeurIPS 2024

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.