Polynomial decision algorithmDeciding in an efficient way weak probabilistic bisimulation in the context of probabilistic automata is an open problem for about a decade. In this work we close this problem by proposing a procedure that checks in polynomial time the existence of a weak combined ...
there is no known polynomial time algorithm for performing them exactly. Fortunately, a number of approximate integration algorithms have been developed, including Markov chain Monte Carlo (MCMC) methods, variational approximations, expectation propagation and sequential Monte Carlo23–26. It is worth not...
Although there had been many probabilistic algorithms for primality testing, there wasn't a deterministic polynomial time algorithm until 2002 when Agrawal, Kayal and Saxena came with an algorithm, popularly known as the AKS algorithm, ... V Menon - 《Computer Science》 被引量: 3发表: 2013年 ...
The condition can be checked in polynomial time with the Bellman-Ford algorithm [16]. \square Proposition 22For a nonnegative cost function c, the canonical p-cause \Theta is {\text {maxcost}}-minimal and {\text {maxcost}}(\Theta ) can be computed in polynomial time.Proof...
We present probabilistic algorithms for the problems of finding an irreducible polynomial of degree n over a finite field, finding roots of a polynomial, and factoring a polynomial into its irreducible factors over a finite field. All of these problems are of importance in algebraic coding theory,...
polynomial time algorithmspartial 2-treetarget nodeslinear timeVarious network reliability problems are #P-complete, however, certain classes of networks such as series-parallel networks, admit polynomial time algorithms. We extend these efficient methods to a superclass of series-parallel networks, the...
The sample and time complexity of algorithms that would be obtained by the above general equivalence, however, are far from optimal. We present a polynomial learning algorithm with a reasonable sample complexity for the important class of convex linear combinations of p-concepts. We also develop ...
Instead of modelling this relationship with, say, a linear parametric function, a there is no known polynomial time algorithm for performing them Gaussian process could be used to learn directly a non-parametric dis- exactly. Fortunately, a number of approximate integration algorithms have tribution ...
Barvinok, A.: A polynomial time algorithm for counting integral points in polyhe- dra when the dimension is fixed. In: FOCS 1993. ACM (1993) 2. Bellare, M., Goldreich, O., Petrank, E.: Uniform generation of NP-witnesses using an NP-oracle. Inf. Comput. 163(2), 510–526 (2000)...
We further extend the algorithm to other families of graphs like Eulerian graphs (and directed regular graphs) and graphs that mix in polynomial time.Our approach is to pseudo-invert the Laplacian, by first "peeling-off" the problematic kernel of the operator, and then to approximate the ...