An algorithm runs inpseudopolynomial timeif the runtime is some polynomialin the numeric value of the input, rather than in the number of bits required to represent it. Our prime testing algorithm is a pseudopolynomial time algorithm, since it runs in time O(n4), but it's not a polynomia...
We show, in this paper, that if an agreeable condition is satisfied, then our problem can be solved by a pseudo-polynomial algorithm with time complexity bounded above by \\(O({n^2}{u_n}{U^2}),where U = {\\Sigma _i}^n{ = _1}{u_i}.\\)...
I have the same question which can be read through this link:https://cs.stackexchange.com/questions/111227/still-not-understanding-why-the-knapsack-problem-does-not-have-a-polynomial-time Could someone explain to me why we don't apply the same logic to the value of n ? I would also like...
Faster Pseudopolynomial Time Algorithms for Subset Sum∗ Konstantinos Koiliaris† Chao Xu‡§ Abstract Given a (multi) set S of n positive integers and a target integer u, the subset sum problem is to decide if there is a subset of S that sums up to u. We present a series of ...
I was studying about pseudo polynomial complexity and I had some doubts. I've seen some topics around and many say that the execution time is related to the size of the input (number of bits to represent the input), I wanted to understand the difference between the knapsack problem and a...
Abstract In this paper, we give aO(logcopt)-approximation algorithm for the point guard problem wherecoptis the optimal number of guards. Our algorithm runs in time polynomial inn, the number of walls of the art gallery and the spreadΔ, which is defined as the ratio between the longest ...
This immediately implies that, despite the fact that there are infinitely many RNA structures of fixed topological genus, the generating function can be reduced to a generating polynomial. We shall refer to this polynomial as the shape polynomial. While the situation is fairly easy for genus 1 [...
L. Adleman, Two theorems on random polynomial time, in 19th Annual Symposium on Foundations of Computer Science, Ann Arbor, Michigan, 16–18 October 1978, pp. 75–83, IEEE Press, New York. Google Scholar ACR97 A. Andreev, A. Clementi, J. Rolim Worst-case hardness suffices for derandomiz...
Our aim is to describe the first pseudo-polynomial time algorithm for total-payoff games in the presence of arbitrary weights. It consists of a non-trivial application of the value iteration paradigm. Indeed, it requires to study, as a milestone, a refinement of these games, called min-cost...
we show how to obtain a pseudorandom generator which satisfies a standard notion of security using onlyO(n4log2(n))bits of randomness if a one-way function with exponential security is given, i.e., a one-way function for which no polynomial time algorithm has probability higher than 2 ...