A joint monotonic encoding layer is designed, which extends isotonic encoding to a joint space through linear interpolation and vector outer products, which allows the model to capture joint effects while ensuring strict joint monotonicity, aligning its output with economic common sense.
Zhe Wang, Rui Wang, Ziyu Guan et al.· Proceedings of the 32nd ACM...· 0 citations
This work proposes Trusted Multi-view learning with Unified Routing (TMUR), which decouples view-specific evidence extraction from fusion arbitration and demonstrates that TMUR consistently improves both classification performance and reliability.
Yi-Lin Zhang, Cai Xu, Haishun Chen et al.· arXiv.org· 0 citations
Calibration-Aware Uncertainty Cascades is proposed, a simple post-hoc framework that independently calibrates each model's confidence and selects deployment policies using validation data and shows theoretically that calibration gives confidence thresholds an explicit selective-risk interpretation, whereas uncalibrated...
Yi-Lin Zhang, Han Jiang, Cai Xu et al.· 0 citations
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