In this paper we present LCSk++: a new metric for measuring the similarity of long strings, and provide an algorithm for its efficient computation. With ever increasing size of strings occuring in practice, e.g. large genomes of plants and animals, classic algorithms such as Longest Common Subsequence (LCS) fail due to demanding computational complexity. Recently, Benson et al. defined a simila...

The cutwidth of a graph G is deened to be the smallest integer k such that the vertices of G can be arranged in a linear layout v 1 ; : : : ; vn] in such a way that for every i = 1; : : : ; n?1, there are at most k edges with the one endpoint in fv 1 ; : : : ; v i g and the other in fv i+1 ; : : : ; vng. In this paper we show how to construct, for any constant k, a linear time algorithm that fo...

The algorithm to compute theory prime implicates, a generalization of prime implicates, in propositional logic has been suggested in [16]. In this paper we have extended that algorithm to compute theory prime implicates of a knowledge base X with respect to another knowledge base Y using [2], where Y is a propositional knowledge base and X |= Y , in modal system T and we have also proved its co...

We propose an algorithm for solving optimization problems defined on a subset of the cone of symmetric positive semidefinite matrices. This algorithm relies on the factorization X = Y Y T , where the number of columns of Y fixes an upper bound on the rank of the positive semidefinite matrix X. It is thus very effective for solving problems that have a low-rank solution. The factorization X = Y ...

We present a randomized algorithm for semi-supervised learning of Mahalanobis metrics over R. The inputs to the algorithm are a set, U> of unlabeled points in R, a set of pairs of points, S = {(x,y)i};x,y G U> that are known to be similar, and a set of pairs of points, D = {(x,y)i}]x,y G [/, that are known to be dissimilar. The algorithm randomly samples 5, D, and m-dimensional subspaces of R a...

We call a minimum cost restricted time combinatorial optimization (MCRT) problem any problem that has a finite set P, finite family S of subsets of P, non-negative threshold h, and two non-negative real-valued functions y : (say, cost) and x : p......-? R+ (say, time). One seeks a solution F* E S with y(F*) min{y(F): F E S, x(F):S h}, where x(G) L:gEGx(g), y(G) = L:gEGy(g) and G E S. We also as...

The butterfly algorithm is a fast algorithm which approximately evaluates a discrete analogue of the integral transform ∫ Rd K(x, y)g(y)dy at large numbers of target points when the kernel, K(x, y), is approximately low-rank when restricted to subdomains satisfying a certain simple geometric condition. In d dimensions with O(Nd) quasi-uniformly distributed source and target points, when each ap...

In this paper, we present a new algorithm, which is based on an efficient heuristic for local search, for rigid protein ± small-molecule docking.We tested our algorithm, called , on the recent 100-complex benchmark , using the conformer generator OMEGA [15] to generate a set of low-energy conformers. The results showed that is competitive both in terms of algorithm efficiency and docking accuracy.

In temporal-logic model checking, we verify the correctness of a program with respect to a desired behavior by checking whether a structure that models the program satis es a temporal-logic formula that speci es the behavior. The main practical limitation of model checking is caused by the size of the state space of the program, which grows exponentially with the number of concurrent components...