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Deterministic approximation algorithms for ranking and clusterings
, 2005
"... We give deterministic versions of randomized approximation algorithms for several ranking and clustering problems that were proposed by Ailon, Charikar and Newman[1]. We show that under a reasonable extension of the triangle inequality in clustering problems, we can resolve Ailon et al.’s open quest ..."
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Cited by 9 (0 self)
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We give deterministic versions of randomized approximation algorithms for several ranking and clustering problems that were proposed by Ailon, Charikar and Newman[1]. We show that under a reasonable extension of the triangle inequality in clustering problems, we can resolve Ailon et al.’s open
Improved deterministic approximation algorithms for Max TSP
 Information Processing Letters
, 2005
"... We present an O(n3)time approximation algorithm for the maximum traveling salesman problem whose approximation ratio is asymptotically 61 81, where n is the number of vertices in the input complete edgeweighted (undirected) graph. We also present an O(n3)time approximation algorithm for the metri ..."
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Cited by 18 (1 self)
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We present an O(n3)time approximation algorithm for the maximum traveling salesman problem whose approximation ratio is asymptotically 61 81, where n is the number of vertices in the input complete edgeweighted (undirected) graph. We also present an O(n3)time approximation algorithm
Deterministic Approximation Algorithms for the Nearest Codeword Problem
 Technical report, Elec. Coll. on Comp. Compl., ECCC
"... Abstract. The Nearest Codeword Problem (NCP) is a basic algorithmic question in the theory of errorcorrecting codes. Given a point v ∈ F n 2 and a linear space L ⊆ F n 2 of dimension k NCP asks to find a point l ∈ L that minimizes the (Hamming) distance from v. It is wellknown that the nearest cod ..."
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Cited by 12 (3 self)
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codeword problem is NPhard. Therefore approximation algorithms are of interest. The best efficient approximation algorithms for the NCP to date are due to Berman and Karpinski. They are a deterministic algorithm that achieves an approximation ratio of O(k/c) for an arbitrary constant c, and a randomized
A deterministic approximation algorithm for the Densest kSubgraph Problem
 International Journal of Operational Research
"... Abstract. In the Densest kSubgraph problem (DSP), we are given an undirected weighted graph G = (V, E) with n vertices (v1,..., vn). We seek to find a subset of k vertices (k belonging to {1,..., n}) which maximizes the number of edges which have their two endpoints in the subset. This problem is N ..."
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Cited by 7 (0 self)
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to apply here because of the cardinality constraint, and can have a high computational cost. In this paper we present a deterministic max(d, 8 9c)approximation algorithm for the Densest kSubgraph Problem (where d is the density of G). The complexity of our algorithm is only the one of linear programming
A deterministic approximation algorithm for computing a permanent of a 0, 1 matrix
, 2008
"... We construct a deterministic approximation algorithm for computing a permanent of a 0, 1 n by n matrix to within a multiplicative factor (1 + ǫ) n, for arbitrary ǫ> 0. When the graph underlying the matrix is a constant degree expander our algorithm runs in polynomial time (PTAS). In the general c ..."
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Cited by 48 (9 self)
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We construct a deterministic approximation algorithm for computing a permanent of a 0, 1 n by n matrix to within a multiplicative factor (1 + ǫ) n, for arbitrary ǫ> 0. When the graph underlying the matrix is a constant degree expander our algorithm runs in polynomial time (PTAS). In the general
A Deterministic Approximation Algorithm for a Minmax Integer Programming Problem
 In Proceedings of the 10th Annual ACMSIAM Symposium on Discrete Algorithms
, 1999
"... We give a deterministic polynomial time approximation algorithm for a minmax integer programming problem, achieving the best existential bound given by Srinivasan [17]. Such a minmax integer programming problem arises naturally from a classical problem on routing to minimize congestion. It also has ..."
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Cited by 7 (1 self)
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We give a deterministic polynomial time approximation algorithm for a minmax integer programming problem, achieving the best existential bound given by Srinivasan [17]. Such a minmax integer programming problem arises naturally from a classical problem on routing to minimize congestion. It also has
Efficient deterministic approximation algorithms for nonmyopic value of information in graphical models
, 2006
"... Abstract — Agents operating in the real world need to handle both uncertainty and resource constraints. Typical problems in this domain are optimization of sequences of observations, and optimal allocation of computation tasks during reasoning and search (also known as metareasoning). In both domai ..."
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Cited by 3 (0 self)
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shaped graph and exact measurements. Suitably relaxing the assumption of exact measurements still allows for a provably close approximation of the optimal subset (of observations) selection, and for approximating the optimal conditional plan. The method is shown to be efficient and to provide a significant
Rounding via Trees: Deterministic Approximation Algorithms for Group Steiner Trees and kmedian
"... ..."
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"... Simple deterministic approximation algorithms ..."
Approximate Signal Processing
, 1997
"... It is increasingly important to structure signal processing algorithms and systems to allow for trading off between the accuracy of results and the utilization of resources in their implementation. In any particular context, there are typically a variety of heuristic approaches to managing these tra ..."
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Cited by 516 (2 self)
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number of ideas and approaches to approximate processing as currently being formulated in the computer science community. We then present four examples of signal processing algorithms/systems that are structured with these goals in mind. These examples may be viewed as partial inroads toward the ultimate
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