Author

Sen-Yu Hou

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Conference Open access Sep 2026

Meta-Cognitive Resonance Label Correction for Instance-Dependent Noise

Training with instance-dependent label noise poses a critical challenge in deep learning, severely impeding model generalization. Existing methods often struggle to break the vicious cycle where corrupted labels degrade feature representations, which in turn impairs noise identification. To overcome this, we propose th...

Gao-Xia Jiang, Jie Su, Sen-Yu Hou et al. · Proceedings of the Thirty-Fi... · 0 citations

Aug 2026

Certainty-Aware Partition and Sufficient Utilization of Noisy Samples

CAPSUN is proposed, a robust framework that improves the precision of clean sample selection and mitigates distribution bias through alignment among subsets, and designs a distribution alignment module to adjust the class distribution contrast of labeled and unlabeled subsets to mitigate class distribution discrepancie...

Jia Zhang, Gao-Xia Jiang, Sen-Yu Hou et al. · Machine-mediated learning · 0 citations