Morphing-based Compression for Data-centric ML Pipelines
Summary: BWARE exploits data-cleaning and feature-engineering structure for workload-aware, lossless matrix compression. It morphs compressed representations directly—without decompression—accelerating end-to-end data-centric ML pipelines from days to hours. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Sebastian Baunsgaard (Berlin Institute for the Foundations of Learning and Data; Technical University of Berlin)
- 2. Matthias Boehm (Berlin Institute for the Foundations of Learning and Data; Technical University of Berlin)
BibTeX Citation
@article{baunsgaard_vldb26,
title = {{Morphing-based Compression for Data-centric ML Pipelines}},
author = {Baunsgaard, Sebastian and Boehm, Matthias},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {3},
pages = {440--454},
doi = {10.14778/3778092.3778104},
url = {https://doi.org/10.14778/3778092.3778104},
year = {2026}
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