Research map / Learning theory and algorithms / Kernels and regression theory
Block-Sample MAC-Bayes Generalization Bounds
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
- How Tight Can PAC-Bayes be in the Small Data Regime? (NeurIPS 2021 · similarity 0.91)
- PAC-Bayes Learning Bounds for Sample-Dependent Priors (NeurIPS 2020 · similarity 0.91)
- PAC-Bayes Un-Expected Bernstein Inequality (NeurIPS 2019 · similarity 0.91)
- PAC-Bayes-Chernoff bounds for unbounded losses (NeurIPS 2024 · similarity 0.90)
- PAC-Bayes Analysis Beyond the Usual Bounds (NeurIPS 2020 · similarity 0.90)
- Controlling Multiple Errors Simultaneously with a PAC-Bayes Bound (NeurIPS 2024 · similarity 0.89)
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.
