Iterative algorithms can be analyzed using a combinatorial diagram basis, which reveals that the asymptotic behavior of these algorithms is dominated by tree-shaped diagrams that represent asymptotically independent Gaussian random variables.
The authors present a faster fully polynomial-time randomized approximation scheme (FPRAS) for the #NFA problem, which is to determine the size of the set of words of a given length accepted by a non-deterministic finite automaton (NFA). The new FPRAS significantly improves the time complexity compared to the previous state-of-the-art FPRAS.
We present a randomized algorithm for the Knapsack problem that runs in time e O(n + t√pmax), where n is the number of items, t is the knapsack capacity, and pmax is the maximum item profit. This improves upon the previous best known e O(n + t · pmax)-time algorithm.
We present a simple and efficient algorithm that computes the composition of two power series in near-linear time complexity, improving upon the previous best algorithms.