Research map / Optimization / Implicit bias and generalization
Local Regularizer Improves Generalization
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
- On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima (ICLR 2017 · similarity 0.90)
- Stochastic Training is Not Necessary for Generalization (ICLR 2022 · similarity 0.89)
- Bad Global Minima Exist and SGD Can Reach Them (NeurIPS 2020 · similarity 0.89)
- Understanding Gradient Regularization in Deep Learning: Efficient Finite-Difference Computation and Implicit Bias (ICML 2023 · similarity 0.89)
- Disentangling the Mechanisms Behind Implicit Regularization in SGD (ICLR 2023 · similarity 0.89)
- Optimal Rates for Generalization of Gradient Descent for Deep ReLU Classification (NeurIPS 2025 · similarity 0.88)
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.