Research map / Label-efficient and robust learning / Noisy labels
Cost-Accuracy Aware Adaptive Labeling 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 |
|---|---|---|---|
| Use adaptive cumulative-accuracy selection instead of the compared selection methods | Active learning with diverse labelers · UCI datasets | test classification accuracy | Helped |
| Select labelers using generalization-bound benefit rather than accuracy-per-cost | Active learning with diverse labelers · UCI datasets | test classification accuracy | Helped |
| Choose the cheapest labeler using CEAL's accuracy-per-cost heuristic | Active learning with diverse labelers · UCI datasets | test classification accuracy | Hurt |
| Use the most accurate labeler for each selected instance | Active learning with diverse labelers · UCI datasets | average label accuracy | Helped |
| Use the most accurate labeler for each selected instance | Active learning with diverse labelers · UCI datasets | cost-effectiveness | Hurt |
| Use AGB when labeler costs and accuracies are close | Active learning with diverse labelers · Focus | test classification accuracy | No clear effect |
Closest papers by meaning
- Re-Active Learning: Active Learning with Relabeling (AAAI 2016 · similarity 0.89)
- Instance-wise Supervision-level Optimization in Active Learning (CVPR 2025 · similarity 0.88)
- Uncertainty Herding: One Active Learning Method for All Label Budgets (ICLR 2025 · similarity 0.88)
- Towards Cost-Effective Learning: A Synergy of Semi-Supervised and Active Learning (CVPR 2025 · similarity 0.86)
- Active Learning with LLMs for Partially Observed and Cost-Aware Scenarios (NeurIPS 2024 · similarity 0.86)
- Contextual Active Model Selection (NeurIPS 2024 · similarity 0.86)
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.