One-Step Abductive Multi-Target Learning with Diverse Noisy Label Samples
- Resource Type
- Working Paper
- Authors
- Yang, Yongquan
- Source
- Subject
- Computer Science - Machine Learning
Computer Science - Artificial Intelligence
- Language
One-step abductive multi-target learning (OSAMTL) was proposed to handle complex noisy labels. In this paper, giving definition of diverse noisy label samples (DNLS), we propose one-step abductive multi-target learning with DNLS (OSAMTL-DNLS) to expand the methodology of original OSAMTL to better handle complex noisy labels.
Comment: 5pages. arXiv admin note: substantial text overlap with arXiv:2110.10325