Showing cs.LGShow all
3 papers · 1 filter
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…
cs.LG2025
Human Guided Learning of Transparent Regression Models
Lukas Pensel, Stefan Kramer
We present a human-in-the-loop (HIL) approach to permutation regression, the novel task of predicting a continuous value for a given ordering of items. The model is a gradient boos…
cs.LG2024
Soft Hoeffding Tree: A Transparent and Differentiable Model on Data Streams
Kirsten Köbschall, Lisa Hartung, Stefan Kramer
We propose soft Hoeffding trees (SoHoT) as a new differentiable and transparent model for possibly infinite and changing data streams. Stream mining algorithms such as Hoeffding tr…