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cs.LG2026
Stochastic Penalty-Barrier Method for Constrained Machine Learning
Adam Bosák, Andrii Kliachkin, Jana Lepšová +4
Constrained Machine Learning (CML) enables fairness-aware training, physics-informed neural networks, and integration of symbolic domain knowledge into statistical models. In this…
cs.LG2026
EVEREST: An Evidential, Tail-Aware Transformer for Rare-Event Time-Series Forecasting
Antanas Zilinskas, Robert N. Shorten, Jakub Marecek
Forecasting rare events in multivariate time-series data is challenging due to severe class imbalance, long-range dependencies, and distributional uncertainty. We introduce EVEREST…