One-Step Abductive Multi-Target Learning with Diverse Noisy Samples.
Yongquan Yang · arXiv (Cornell University) · 2021
One-step abductive multi-target learning (OSAMTL) was proposed to handle complex noisy labels. In this paper, giving definition of diverse noisy samples (DNS), we propose one-step abductive multi-target learning with DNS (OSAMTL-DNS) to expand the original OSAMTL to a wider range of tasks that handle complex noisy labels.