Mixed integer programming formulation of unsupervised learning

This addresses a theoretical challenge in unsupervised learning for researchers, but it is incremental as it builds on existing Boltzmann machine methods.

The authors tackled the problem of training full Boltzmann machines by formulating it as a mixed binary quadratic feasibility problem, and they tested this approach analytically and numerically on XOR patterns, showing it works as a proof of concept.