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cs.LG2026
Unsupervised Anomaly Detection in Process-Complex Industrial Time Series: A Real-World Case Study
Sergej Krasnikov, Lukas Meitz, Samineh Bagheri +3
Industrial time-series data from real production environments exhibits substantially higher complexity than commonly used benchmark datasets, primarily due to heterogeneous, multi-…
cs.NE2026★ 1 cited
Pareto-Optimal Anytime Algorithms via Bayesian Racing
Jonathan Wurth, Helena Stegherr, Neele Kemper +2
Selecting an optimization algorithm requires comparing candidates across problem instances, but the computational budget for deployment is often unknown at benchmarking time. Curre…