Scalable Algorithms for Approximate DNF Model Counting
A new Monte Carlo approach with an adaptive stopping rule and short-circuit formula evaluation is developed that achieves Probably Approximately Correct (PAC) learning bounds and has asymptotically improved time and randomness complexity compared to previous methods.
Paul Burkhardt, David G. Harris, Kevin Schmitt
· Proceedings of the Thirty-Fi... · 0 citations