Results 1  10
of
192
Randomized Algorithms
, 1995
"... Randomized algorithms, once viewed as a tool in computational number theory, have by now found widespread application. Growth has been fueled by the two major benefits of randomization: simplicity and speed. For many applications a randomized algorithm is the fastest algorithm available, or the simp ..."
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Cited by 1884 (38 self)
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Randomized algorithms, once viewed as a tool in computational number theory, have by now found widespread application. Growth has been fueled by the two major benefits of randomization: simplicity and speed. For many applications a randomized algorithm is the fastest algorithm available, or the simplest, or both. A randomized algorithm is an algorithm that uses random numbers to influence the choices it makes in the course of its computation. Thus its behavior (typically quantified as running time or quality of output) varies from
Biclustering of Expression Data
, 2000
"... An efficient nodedeletion algorithm is introduced to find submatrices... ..."
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Cited by 392 (0 self)
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An efficient nodedeletion algorithm is introduced to find submatrices...
Easy Problems for TreeDecomposable Graphs
, 1991
"... this paper are (i) a construction by which, for a given bounded treewidth, a general MS graph property P is transformed to an MS binary tree property r(P), and a general labeled graph G with a suitable treedecomposition is transformed to a labeled binary tree T(G) in time linear in the number of v ..."
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Cited by 233 (6 self)
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this paper are (i) a construction by which, for a given bounded treewidth, a general MS graph property P is transformed to an MS binary tree property r(P), and a general labeled graph G with a suitable treedecomposition is transformed to a labeled binary tree T(G) in time linear in the number of vertices of G and in such a way that P holds for G if and only if r(P) holds for T(G). This allows us, using techniques developed by Doner [20] and Thatcher and Wright [42], to compile a tree automaton which decides the MSproblem r(P) on the tree T(G) (and thus also P on the graph G) in linear time, and (ii) a procedure whereby such an automaton for a MS formula with free variables is modified to solve a related EMS problem involving counting
An analysis of BGP convergence properties
 In SIGCOMM
"... The Border Gateway Protocol (BGP) is the de facto interdomain routing protocol used to exchange reachability information between Autonomous Systems in the global Internet. BGP is a pathvector protocol that allows each Autonomous System to override distancebased metrics with policybased metrics wh ..."
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Cited by 213 (14 self)
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The Border Gateway Protocol (BGP) is the de facto interdomain routing protocol used to exchange reachability information between Autonomous Systems in the global Internet. BGP is a pathvector protocol that allows each Autonomous System to override distancebased metrics with policybased metrics when choosing best routes. Varadhan et al. [18] have shown that it is possible for a group of Autonomous Systems to independently define BGP policies that together lead to BGP protocol oscillations that never converge on a stable routing. One approach to addressing this problem is based on static analysis of routing policies to determine if they are safe. We explore the worstcase complexity for convergenceoriented static analysis of BGP routing policies. We present an abstract model of BGP and use it to define several global sanity conditions on routing policies that are related to BGP convergence/divergence. For each condition we show that the complexity of statically checking it is either NPcomplete or NPhard. 1
Boundedwidth polynomialsize branching programs recognize exactly those languages
 in NC’, in “Proceedings, 18th ACM STOC
, 1986
"... We show that any language recognized by an NC ’ circuit (fanin 2, depth O(log n)) can be recognized by a width5 polynomialsize branching program. As any boundedwidth polynomialsize branching program can be simulated by an NC ’ circuit, we have that the class of languages recognized by such prog ..."
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Cited by 213 (14 self)
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We show that any language recognized by an NC ’ circuit (fanin 2, depth O(log n)) can be recognized by a width5 polynomialsize branching program. As any boundedwidth polynomialsize branching program can be simulated by an NC ’ circuit, we have that the class of languages recognized by such programs is exactly nonuniform NC’. Further, following
Approximation schemes for covering and packing problems in image processing and VLSI
 J. ACM
, 1985
"... Abstract. A unified and powerful approach is presented for devising polynomial approximation schemes for many strongly NPcomplete problems. Such schemes consist of families of approximation algorithms for each desired performance bound on the relative error c> 0, with running time that is polyno ..."
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Cited by 192 (0 self)
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Abstract. A unified and powerful approach is presented for devising polynomial approximation schemes for many strongly NPcomplete problems. Such schemes consist of families of approximation algorithms for each desired performance bound on the relative error c> 0, with running time that is polynomial when c is fixed. Thougb the polynomiality of these algorithms depends on the degree of approximation e being fixed, they cannot be improved, owing to a negative result stating that there are no fully polynomial approximation schemes for strongly NPcomplete problems unless NP = P. The unified technique that is introduced here, referred to as the shifting strategy, is applicable to numerous geometric covering and packing problems. The method of using the technique and how it varies with problem parameters are illustrated. A similar technique, independently devised by B. S. Baker, was shown to be applicable for covering and packing problems on planar graphs.
Interactive proofs and the hardness of approximating cliques
 Journal of the ACM
, 1996
"... The contribution of this paper is twofold. First, a connection is shown between approximating the size of the largest clique in a graph and multiprover interactive proofs. Second, an efficient multiprover interactive proof for NP languages is constructed, where the verifier uses very few random b ..."
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Cited by 157 (11 self)
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The contribution of this paper is twofold. First, a connection is shown between approximating the size of the largest clique in a graph and multiprover interactive proofs. Second, an efficient multiprover interactive proof for NP languages is constructed, where the verifier uses very few random bits and communication bits. Last, the connection between cliques and efficient multiprover interactive proofs, is shown to yield hardness results on the complexity of approximating the size of the largest clique in a graph. Of independent interest is our proof of correctness for the multilinearity test of functions. 1
Identifying the minimal transversals of a hypergraph and related problems
 SIAM Journal on Computing
, 1995
"... The paper considers two decision problems on hypergraphs, hypergraph saturation and recognition of the transversal hypergraph, and discusses their significance for several search problems in applied computer science. Hypergraph saturation, i.e., given a hypergraph H, decide if every subset of vertic ..."
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Cited by 125 (7 self)
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The paper considers two decision problems on hypergraphs, hypergraph saturation and recognition of the transversal hypergraph, and discusses their significance for several search problems in applied computer science. Hypergraph saturation, i.e., given a hypergraph H, decide if every subset of vertices is contained in or contains some edge of H, is shown to be coNPcomplete. A certain subproblem of hypergraph saturation, the saturation of simple hypergraphs, is shown to be computationally equivalent to transversal hypergraph recognition, i.e., given two hypergraphs H 1; H 2, decide if the sets in H 2 are all the minimal transversals of H 1. The complexity of the search problem related to the recognition of the transversal hypergraph, the computation of the transversal hypergraph, is an open problem. This task needs time exponential in the input size, but it is unknown whether an outputpolynomial algorithm exists for this problem. For several important subcases, for instance if an upper or lower bound is imposed on the edge size or for acyclic hypergraphs, we present outputpolynomial algorithms. Computing or recognizing the minimal transversals of a hypergraph is a frequent problem in practice, which is pointed out by identifying important applications in database theory, Boolean switching theory, logic, and AI, particularly in modelbased diagnosis.
A FASTER STRONGLY POLYNOMIAL MINIMUM COST FLOW ALGORITHM
, 1991
"... In this paper, we present a new strongly polynomial time algorithm for the minimum cost flow problem, based on a refinement of the EdmondsKarp scaling technique. Our algorithm solves the uncapacitated minimum cost flow problem as a sequence of O(n log n) shortest path problems on networks with n no ..."
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Cited by 116 (10 self)
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In this paper, we present a new strongly polynomial time algorithm for the minimum cost flow problem, based on a refinement of the EdmondsKarp scaling technique. Our algorithm solves the uncapacitated minimum cost flow problem as a sequence of O(n log n) shortest path problems on networks with n nodes and m arcs and runs in O(n log n (m + n log n)) time. Using a standard transformation, thjis approach yields an O(m log n (m + n log n)) algorithm for the capacitated minimum cost flow problem. This algorithm improves the best previous strongly polynomial time algorithm, due to Z. Galil and E. Tardos, by a factor of n 2 /m. Our algorithm for the capacitated minimum cost flow problem is even more efficient if the number of arcs with finite upper bounds, say n', is much less than m. In this case, the running time of the algorithm is O((m ' + n)log n(m + n log n)).
Hardness Of Approximations
, 1996
"... This chapter is a selfcontained survey of recent results about the hardness of approximating NPhard optimization problems. ..."
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Cited by 102 (4 self)
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This chapter is a selfcontained survey of recent results about the hardness of approximating NPhard optimization problems.