3 papers
cs.LG2026
Towards Stream Learning on Embedded Systems: Benchmarking the Memory Consumption of Stream Learning Methods
Sebastian Buschjäger, Nuwan Gunasekara, Heitor Murilo Gomes
Stream learning is commonly evaluated through predictive performance and adaptation to concept drift. However, sustained operation of a stream learner also requires predictable and…
cs.LG2026
Pruning Extensions and Efficiency Trade-Offs for Sustainable Time Series Classification
Raphael Fischer, Angus Dempster, Sebastian Buschjäger +3
Time series classification (TSC) enables important use cases, however lacks a unified understanding of performance trade-offs across models, datasets, and hardware. While resource…
cs.LG2025
Lift What You Can: Green Online Learning with Heterogeneous Ensembles
Kirsten Köbschall, Sebastian Buschjäger, Raphael Fischer +2
Ensemble methods for stream mining necessitate managing multiple models and updating them as data distributions evolve. Considering the calls for more sustainability, established m…