Reinforcement learning for adaptive interior point methods in convex quadratic programming

Jeremy Bertoncini, Alberto De Marchi, Matthias Gerdts +1

Quadratic programming is a workhorse of modern nonlinear optimization, control, and data science. Although regularized methods offer convergence guarantees under minimal assumption…