Title: Hybrid restricted master problem for Boolean matrix factorisation Show Chinese title

Title: 布尔矩阵分解的混合受限主问题

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. Show Chinese abstract

Abstract: 我们提出bfact，一个用于执行精确低秩布尔矩阵分解（BMF）的Python包。 bfact使用一种混合组合优化方法，该方法基于从聚类算法生成的先验候选因子。 它在执行第二次组合或启发式算法以恢复BMF之前选择最佳不相交因子。 我们表明，bfact在模拟设置中特别擅长估计矩阵的真实秩。 在真实基准测试中，使用来自人类肺部细胞图谱的单细胞RNA测序数据集的汇总数据，我们表明bfact实现了强大的信号恢复，并且具有更低的秩。