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We present BackboneLearn: an open-source software package and framework forscaling mixed-integer optimization (MIO) problems with indicator variables tohigh-dimensional problems. This optimization paradigm can naturally be used toformulate fundamental problems in interpretable supervised learning (e.g.,sparse regression and decision trees), in unsupervised learning (e.g.,clustering), and beyond; BackboneLearn solves the aforementioned problemsfaster than exact methods and with higher accuracy than commonly usedheuristics. The package is built in Python and is user-friendly and easilyextensible: users can directly implement a backbone algorithm for their MIOproblem at hand. The source code of BackboneLearn is available on GitHub (link:https://github.com/chziakas/backbone_learn).

BackboneLearn: A Library for Scaling Mixed-Integer Optimization-Based Machine Learning