The EL-MIATTs framework offers LAF-grounded evaluation and UTTL-grounded learning strategies to handle multiple inaccurate true targets in machine learning under uncertain supervision.
Are Labels Always Necessary for Classifier Accuracy Evaluation? Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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LAF-Based Evaluation and UTTL-Based Learning Strategies with MIATTs
The EL-MIATTs framework offers LAF-grounded evaluation and UTTL-grounded learning strategies to handle multiple inaccurate true targets in machine learning under uncertain supervision.
- Negative Ontology of True Target for Machine Learning: Towards Evaluation and Learning under Democratic Supervision