Yuru Ren

Noisy Multi-Label Learning through Co-Occurrence-Aware Diffusion

Noisy labels often compel models to overfit, especially in multi-label classification tasks. Existing methods for noisy multi-label learning (NML) primarily follow a discriminative paradigm, which relies on noise transition matrix estimation or small-loss strategies to correct noisy labels. However,…