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Approximation Algorithms and Heuristics for the Dynamic Storage Allocation Problem
 UNIV. MARYLAND INST. ADV. COMPUT. STUDIES, COLLEGE PARK
, 1999
"... In this report, we look at the problem of packing a number of arrays in memory efficiently. This is known as the dynamic storage allocation problem (DSA) and it is known to be NPcomplete. We develop some simple, polynomialtime approximation algorithms with the best of them achieving a bound of 4 f ..."
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Cited by 4 (4 self)
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In this report, we look at the problem of packing a number of arrays in memory efficiently. This is known as the dynamic storage allocation problem (DSA) and it is known to be NPcomplete. We develop some simple, polynomialtime approximation algorithms with the best of them achieving a bound of 4
A PolynomialTime Approximation Algorithm for the Permanent of a Matrix with NonNegative Entries
 JOURNAL OF THE ACM
, 2004
"... We present a polynomialtime randomized algorithm for estimating the permanent of an arbitrary n ×n matrix with nonnegative entries. This algorithm—technically a “fullypolynomial randomized approximation scheme”—computes an approximation that is, with high probability, within arbitrarily small spec ..."
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Cited by 427 (27 self)
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We present a polynomialtime randomized algorithm for estimating the permanent of an arbitrary n ×n matrix with nonnegative entries. This algorithm—technically a “fullypolynomial randomized approximation scheme”—computes an approximation that is, with high probability, within arbitrarily small
Approximation Algorithms for Intersection Graphs
, 2009
"... We introduce three new complexity parameters that in some sense measure how chordallike a graph is. The similarity to chordal graphs is used to construct simple polynomialtime approximation algorithms with constant approximation ratio for many NPhard problems, when restricted to graphs for which ..."
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Cited by 8 (0 self)
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We introduce three new complexity parameters that in some sense measure how chordallike a graph is. The similarity to chordal graphs is used to construct simple polynomialtime approximation algorithms with constant approximation ratio for many NPhard problems, when restricted to graphs for which
Polynomial time approximation schemes for Euclidean traveling salesman and other geometric problems
 Journal of the ACM
, 1998
"... Abstract. We present a polynomial time approximation scheme for Euclidean TSP in fixed dimensions. For every fixed c Ͼ 1 and given any n nodes in 2 , a randomized version of the scheme finds a (1 ϩ 1/c)approximation to the optimum traveling salesman tour in O(n(log n) O(c) ) time. When the nodes ..."
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Cited by 397 (2 self)
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to Christofides) achieves a 3/2approximation in polynomial time. We also give similar approximation schemes for some other NPhard Euclidean problems: Minimum Steiner Tree, kTSP, and kMST. (The running times of the algorithm for kTSP and kMST involve an additional multiplicative factor k.) The previous best
Improved Approximation Algorithms for Maximum Cut and Satisfiability Problems Using Semidefinite Programming
 Journal of the ACM
, 1995
"... We present randomized approximation algorithms for the maximum cut (MAX CUT) and maximum 2satisfiability (MAX 2SAT) problems that always deliver solutions of expected value at least .87856 times the optimal value. These algorithms use a simple and elegant technique that randomly rounds the solution ..."
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Cited by 1211 (13 self)
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We present randomized approximation algorithms for the maximum cut (MAX CUT) and maximum 2satisfiability (MAX 2SAT) problems that always deliver solutions of expected value at least .87856 times the optimal value. These algorithms use a simple and elegant technique that randomly rounds
Optimal Aggregation Algorithms for Middleware
 IN PODS
, 2001
"... Assume that each object in a database has m grades, or scores, one for each of m attributes. For example, an object can have a color grade, that tells how red it is, and a shape grade, that tells how round it is. For each attribute, there is a sorted list, which lists each object and its grade under ..."
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Cited by 717 (4 self)
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simple algorithm (“the threshold algorithm”, or TA) that is optimal in a much stronger sense than FA. We show that TA is essentially optimal, not just for some monotone aggregation functions, but for all of them, and not just in a highprobability worstcase sense, but over every database. Unlike FA
Factor Graphs and the SumProduct Algorithm
 IEEE TRANSACTIONS ON INFORMATION THEORY
, 1998
"... A factor graph is a bipartite graph that expresses how a "global" function of many variables factors into a product of "local" functions. Factor graphs subsume many other graphical models including Bayesian networks, Markov random fields, and Tanner graphs. Following one simple c ..."
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Cited by 1791 (69 self)
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computational rule, the sumproduct algorithm operates in factor graphs to computeeither exactly or approximatelyvarious marginal functions by distributed messagepassing in the graph. A wide variety of algorithms developed in artificial intelligence, signal processing, and digital communications can
Angeles
"... In this report, we look at the problem of packing a number of arrays in memory efficiently. This is known as the dynamic storage allocation problem (DSA) and it is known to be NPcomplete. We develop some simple, polynomialtime approximation algorithms with the best of them achieving a bound of 4 f ..."
Abstract
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In this report, we look at the problem of packing a number of arrays in memory efficiently. This is known as the dynamic storage allocation problem (DSA) and it is known to be NPcomplete. We develop some simple, polynomialtime approximation algorithms with the best of them achieving a bound of 4
An Experimental Comparison of MinCut/MaxFlow Algorithms for Energy Minimization in Vision
 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 2001
"... After [10, 15, 12, 2, 4] minimum cut/maximum flow algorithms on graphs emerged as an increasingly useful tool for exact or approximate energy minimization in lowlevel vision. The combinatorial optimization literature provides many mincut/maxflow algorithms with different polynomial time compl ..."
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Cited by 1315 (53 self)
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After [10, 15, 12, 2, 4] minimum cut/maximum flow algorithms on graphs emerged as an increasingly useful tool for exact or approximate energy minimization in lowlevel vision. The combinatorial optimization literature provides many mincut/maxflow algorithms with different polynomial time
A Singular Value Thresholding Algorithm for Matrix Completion
, 2008
"... This paper introduces a novel algorithm to approximate the matrix with minimum nuclear norm among all matrices obeying a set of convex constraints. This problem may be understood as the convex relaxation of a rank minimization problem, and arises in many important applications as in the task of reco ..."
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Cited by 555 (22 self)
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This paper introduces a novel algorithm to approximate the matrix with minimum nuclear norm among all matrices obeying a set of convex constraints. This problem may be understood as the convex relaxation of a rank minimization problem, and arises in many important applications as in the task
Results 1  10
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