Optimization Algorithm Ranking Preservation Using Surrogate Models in the MECHBench Framework
E. Raponi, I. Olarte, Rodriguez
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Exposing Blind Spots in Deep Imbalanced Regression Evaluation
The results show that standard virtual-sensing models exhibit substantial tail degradation hidden by global MAE, that existing DIR methods can improve balanced performance but transfer unevenly to multimodal time-series data, and that tail-region instability remains a largely hidden failure mode under current DIR evalu...
Noah C. Puetz, Jens U. Brandt, M. Hilbert et al.
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Reliable Virtual Sensing: A Multi-Domain Benchmark for Robustness Under Sensor Failures
It is argued that real-world deployment demands robustness and introduced MuViS-C, the first multi-domain benchmark of robustness against common sensor failures in learning-based virtual sensing, which covers ten sensor failure modes, from subtle drifts to catastrophic signal dropouts, at multiple severities.
Jens U. Brandt, Noah C. Puetz, Alexander Windmann et al.
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