Research map / Label-efficient and robust learning / Recognition and long-tail
Search Improves Label for Active Learning
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.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Adding a SEARCH oracle alongside the standard LABEL oracle in active learning | active learning algorithm · theoretical analysis | label complexity (problem-dependent) | Helped |
Closest papers by meaning
- Active Learning with Oracle Epiphany (NeurIPS 2016 · similarity 0.90)
- Asking the Right Questions to the Right Users: Active Learning with Imperfect Oracles (AAAI 2020 · similarity 0.90)
- Active Learning from Imperfect Labelers (NeurIPS 2016 · similarity 0.88)
- The Power of Comparisons for Actively Learning Linear Classifiers (NeurIPS 2020 · similarity 0.87)
- Active Learning From Positive and Unlabeled Examples (NeurIPS 2026 · similarity 0.84)
- Uncertainty Herding: One Active Learning Method for All Label Budgets (ICLR 2025 · 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.