BBOmix: A Tabular Benchmark for Hyperparameter Optimization of Unsupervised Biological Representation Learning
- Published
- Source
- arXiv
- Paper number
- 317
- Field
- Machine Learning
- arXiv ID
- 2606.05139
Key points
- Deep unsupervised learning architectures, especially autoencoders, are increasingly used in this field for dimensionality reduction and representation learning.
- To make large-scale unsupervised HPO research broadly accessible, the paper introduces BBOmix, the first open-source tabular benchmark for unsupervised representation learning on real biological data.
- The benchmark includes 105,000 evaluations across four AE architectures and seven multi-omics modalities in the TCGA and SCHC datasets.
Paper links
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