The Aho-Corasick algorithm derives a failure deterministic finite automaton for finding matches of a finite set of keywords in a text. It has the minimum number of transitions needed for this task. The DFA-Homomorphic Algorithm (DHA) algorithm is more general, deriving from an arbitrary complete deterministic finite automaton a language-equivalent failure deterministic finite automaton. DHA tak...

Following ideas from [Hei83, DFGS91, MT97] and applying the techniques proposed in [May89, KM96, Küh98], we present a deterministic algorithm for computing the dimension of a polynomial ideal requiring polynomial working space.

Various techniques exist to solve the non-convex optimization problem of clustering. Recent developments have employed a deterministic annealing approach to solving this problem. In this letter a new approximation clustering algorithm, incorporating a gradient descent technique with deterministic annealing, is described. Results are presented for this new method, and its performance is compared...

A dynamic network is a communication network whose communication structure can evolve over time. The dynamic diameter is the counterpart of the classical static diameter, it is the maximum time needed for a node to causally influence any other node in the network. We consider the problem of computing the dynamic diameter of a given dynamic network. If the evolution is known a priori, that is if...

Given a square, nonsingular matrix of univariate polynomials F ∈ K[x]n×n over a field K, we give a deterministic algorithm for finding the determinant of F. The complexity of the algorithm is O ̃(nωs) field operations where s is the average column degree or the average row degree of F. Here O ̃ notation is Big-O with log factors omitted and ω is the exponent of matrix multiplication.

We study the problems of permutation routing and sorting on several models of meshes with xed and reconngurable row and column buses. We describe two fast and fairly simple deterministic algorithms for permutation routing on two-dimensional networks, and a more complicated algorithm for multi-dimensional networks. The algorithms are obtained by converting two known oo-line routing schemes into ...

We study the convergence and asymptotic normality of a generalized form of stochastic approximation algorithm with deterministic perturbation sequences. Both one-simulation and two-simulation methods are considered. Assuming a special structure of deterministic sequence, we establish sufficient condition on the noise sequence for a.s. convergence of the algorithm. Construction of such a special...

We prove the existence of a canonical form for semi-deterministic transducers with sets of pairwise incomparable output strings. Based on this, we develop an algorithm which learns semi-deterministic transducers given access to translation queries. We also prove that there is no learning algorithm for semi-deterministic transducers that uses only domain knowledge.

The paper introduces a hybrid Tabu Search-Evolutionary Algorithm for solving the constraint satisfaction problem, called STLEA. Extensive experimental fine-tuning of parameters of the algorithm was performed to optimise the performance of the algorithm on a commonly used test-set. The performance of the STLEA was then compared to the best known evolutionary algorithm and benchmark deterministic...