Matrix decompositions are used for many data mining purposes. One of these purposes is to find a concise but interpretable
representation of a given data matrix. Different decomposition formulations have been proposed for this task, many of which
assume a certain property of the input data (e.g., nonnegativity) and aim at preserving that property in the decomposition.
This is an extended abstract of an article published in the Data Mining and Knowledge Discovery journal [1].