Research map / Label-efficient and robust learning / Noisy labels
Explicit Regularisation in Gaussian Noise Injections
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
- Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections (ICML 2021 · similarity 0.89)
- On the Inherent Regularization Effects of Noise Injection During Training (ICML 2021 · similarity 0.88)
- Noise Injection Node Regularization for Robust Learning (ICLR 2023 · similarity 0.86)
- Regularizing Deep Neural Networks by Noise: Its Interpretation and Optimization (NeurIPS 2017 · similarity 0.86)
- Ghost Noise for Regularizing Deep Neural Networks (AAAI 2024 · similarity 0.85)
- Generalization in Kernel Regression Under Realistic Assumptions (ICML 2024 · similarity 0.84)
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.
