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Stefan Oehmcke

2 accepted papers

2026

Boosted Trees on a Diet: Compact Models for Resource-Constrained Devices

ICLR 2026poster

Deploying machine learning models on compute-constrained devices has become a key building block of modern IoT applications. In this work, we present a compression scheme for boosted decision trees, addressing the growing need for lightweight machine learning models. Specifically, we provide techniq…

Cited by 0SourceScholar
2024

MMEarth: Exploring Multi-Modal Pretext Tasks For Geospatial Representation Learning

ECCV 2024poster

"The volume of unlabelled Earth observation (EO) data is huge, but many important applications lack labelled training data. However, EO data offers the unique opportunity to pair data from different modalities and sensors automatically based on geographic location and time, at virtually no human lab…