The complexity class PP consists of all decision problems solvable by polynomial-time probabilistic Turing machines. It is well known that PP is a highly intractable complexity class and that… (More)

The study of phase transitions in algorithmic problems has revealed that usually the critical value of the constrainedness parameter at which the phase transition occurs coincides with the value at… (More)

We introduce NL, a learning algorithm for inferring non-deterministic finite-state automata using membership and equivalence queries. More specifically, residual finite-state automata (RFSA) are… (More)

The complexity class PP consists of all decision problems solvable by polynomial-time probabilistic Turing machines. It is well known that PP is a highly intractable complexity class and that… (More)