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arXiv · 2509.06192

Hybrid restricted master problem for Boolean matrix factorisation

Ellen Visscher·Michael Forbes·Christopher Yau
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Abstract

We present bfact, a Python package for performing accurate low-rank Boolean matrix factorisation (BMF). bfact uses a hybrid combinatorial optimisation approach based on a priori candidate factors generated from clustering algorithms. It selects the best disjoint factors before performing either a second combinatorial or heuristic algorithm to recover the BMF. We show that bfact does particularly well at estimating the true rank of matrices in simulated settings. In real benchmarks, using a collation of single-cell RNA-sequencing datasets from the Human Lung Cell Atlas, we show that bfact achieves strong signal recovery, with a much lower rank.

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Ellen Visscher, Michael Forbes, Christopher Yau. 2025-09-07. Hybrid restricted master problem for Boolean matrix factorisation. https://arxiv.org/abs/2509.06192

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