Solving combinatorial optimization problems using quantum or quantum-inspired machine learning models would benefit from strategies able to work with arbitrary objective functions. Here, the authors use the power of generative models to realise such a black-box solver, and show promising performances on some portfolio optimization examples.
- Javier Alcazar
- Mohammad Ghazi Vakili
- Alejandro Perdomo-Ortiz
