Author

Jie Xu

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#machine learning Preprint May 2025

Understanding and Mitigating Under-Confidence in GNNs from the Final Layer

It is theoretically show that reducing the weight decay of the final-layer parameters alleviates GNN under-confidence by acting on the class-centroid level, while node-level calibration acts as a finer-grained complement to class-centroid-level calibration, which encourages each test node to be closer to its predicted...

Jincheng Huang, Jie Xu, Xiao-Shuang Shi et al. · 6 citations

Conference Open access Sep 2026

Salient-Residual Decoupled Multi-View Learning for Clustering

This paper proposes salient-residual decoupled multi-view learning for clustering, SRDMVC, introducing a novel decomposition-fusion iterative optimization, which separates the feature space into a salient space and a residual subspace effectively and fuses them using a novel attention mechanism.

Gao-Kai Wang, Yazhou Ren, Feng-Yu Zhang et al. · Proceedings of the Thirty-Fi... · 0 citations