Binary matrix factorization (BMF) is a topic having applications in the areas of data mining, machine learning, and bioinformatics and has been recently gathering attraction in the theoretical computer science community. In BMF, we are given a matrix \(A\in \{0,1\}^{m\times n}\) and a positive integer k, and we want to find matrices \(U\in \{0,1\} ^{m\times k}\) and \(V\in \{0,1\}^{k\times n}\) such that \(||A-U\boldsymbol\cdot V||_p\) is minimized for some \(p\ge 0\). Depending on the choice of the arithmetic for the multiplication \(U\boldsymbol\cdot V\) and the choice of the norm \(||\dots ||_p\), we obtain different problems. The most commonly used arithmetics are boolean arithmetic, standard integer arithmetic and GF(2) arithmetic, and the most commonly used norms are \(\ell_0,\ell_1\) and \(\ell_2\).