Research map / Learning theory and algorithms / Kernels and regression theory
Scaling Laws for Precision in High-Dimensional Linear Regression
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- Scaling Laws for Precision (ICLR 2025 · similarity 0.90)
- Scaling Laws in Linear Regression: Compute, Parameters, and Data (NeurIPS 2024 · similarity 0.89)
- Improved Scaling Laws in Linear Regression via Data Reuse (NeurIPS 2025 · similarity 0.89)
- Learning with Synthetic Data via SGD in High-Dimensional Linear Regression (NeurIPS 2026 · similarity 0.88)
- Unified Scaling Laws for Compressed Representations (NeurIPS 2025 · similarity 0.88)
- Power Lines: Scaling laws for weight decay and batch size in LLM pre-training (NeurIPS 2025 · similarity 0.87)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.