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Approximating Minsum Set Cover
, 2003
"... this paper appeared in the conference proceedings of APPROX 2002 ..."
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Cited by 73 (2 self)
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this paper appeared in the conference proceedings of APPROX 2002
A Threshold of ln n for Approximating Set Cover
 JOURNAL OF THE ACM
, 1998
"... Given a collection F of subsets of S = f1; : : : ; ng, set cover is the problem of selecting as few as possible subsets from F such that their union covers S, and max kcover is the problem of selecting k subsets from F such that their union has maximum cardinality. Both these problems are NPhar ..."
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Cited by 766 (5 self)
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hard. We prove that (1 \Gamma o(1)) ln n is a threshold below which set cover cannot be approximated efficiently, unless NP has slightly superpolynomial time algorithms. This closes the gap (up to low order terms) between the ratio of approximation achievable by the greedy algorithm (which is (1 \Gamma
Average minsum decoding of LDPC codes
 5th International Symposium on Turbo Codes and Related Topics
, 2008
"... Abstract—Simulations have shown that the outputs of minsum (MS) decoding generally behave in one of two ways: the output either eventually stabilizes at a codeword or eventually cycles through a finite set of vectors that may include both codewords and noncodewords. This inconsistency in MS across ..."
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Cited by 1 (1 self)
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iterations has significantly contributed to the difficulty in studying the performance of this decoder. To overcome this problem, a new decoder, average minsum (AMS), is proposed; this decoder outputs the average of the minsum output vectors over a finite set of iterations. Simulations comparing MS, AMS
Some optimal inapproximability results
, 2002
"... We prove optimal, up to an arbitrary ffl? 0, inapproximability results for MaxEkSat for k * 3, maximizing the number of satisfied linear equations in an overdetermined system of linear equations modulo a prime p and Set Splitting. As a consequence of these results we get improved lower bounds for ..."
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Cited by 748 (11 self)
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for the efficient approximability of many optimization problems studied previously. In particular, for MaxE2Sat, MaxCut, MaxdiCut, and Vertex cover. Warning: Essentially this paper has been published in JACM and is subject to copyright restrictions. In particular it is for personal use only.
Approximation Algorithms for MinSum kClustering and Balanced kMedian
"... We consider two closely related fundamental clustering problems in this paper. In the minsum kclustering one is given a metric space and has to partition the points into k clusters while minimizing the sum of pairwise distances between the points within the clusters. In the Balanced kMedian probl ..."
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We consider two closely related fundamental clustering problems in this paper. In the minsum kclustering one is given a metric space and has to partition the points into k clusters while minimizing the sum of pairwise distances between the points within the clusters. In the Balanced k
Approximation Algorithms for MinSum PClustering
 Discrete Applied Mathematics
, 1998
"... We consider the following problem: Given a graph with edge lengths satisfying the triangle inequality, partition its node set into p subsets, minimizing the total length of edges whose two ends are in the same subset. For this problem we present an approximation algorithm which comes to at most twic ..."
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Cited by 15 (3 self)
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the triangle inequality. The minsum pclustering problem requires to partition V into p subsets, possibly of given sizes, minimizing the total length of edges whose two ends are in the same subset. The problem has numerous applications in various areas (see, for example, [2, 3, 4, 5]). In this paper we
Polyline fitting of planar points under minsum criteria
 ATLANTA, GA: U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES, PUBLIC HEALTH SERVICE
, 1998
"... Fitting a curve of a certain type to a given set of points in the plane is a basic problem in statistics and has numerous applications. We consider fitting a polyline with k joints under the minsum criteria with respect to L1 and L2metrics, which are more appropriate measures than uniform and Hau ..."
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Cited by 8 (0 self)
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Fitting a curve of a certain type to a given set of points in the plane is a basic problem in statistics and has numerous applications. We consider fitting a polyline with k joints under the minsum criteria with respect to L1 and L2metrics, which are more appropriate measures than uniform
Duplicate Record Detection: A Survey
, 2007
"... Often, in the real world, entities have two or more representations in databases. Duplicate records do not share a common key and/or they contain errors that make duplicate matching a difficult task. Errors are introduced as the result of transcription errors, incomplete information, lack of standa ..."
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Cited by 431 (11 self)
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of standard formats, or any combination of these factors. In this paper, we present a thorough analysis of the literature on duplicate record detection. We cover similarity metrics that are commonly used to detect similar field entries, and we present an extensive set of duplicate detection algorithms
Minsum clustering of protein sequences with limited distance information
 In Proc. of the 1st International Workshop on SimilarityBased Pattern Analysis and Recognition (SIMBAD
, 2011
"... Abstract. We study the problem of efficiently clustering protein sequences in a limited information setting. We assume that we do not know the distances between the sequences in advance, and must query them during the execution of the algorithm. Our goal is to find an accurate clustering using few q ..."
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Cited by 2 (1 self)
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such as BLAST, which compares an input sequence to an entire data set. Given a natural assumption about the approximation stability of the minsum objective function for clustering, we design a provably accurate clustering algorithm that uses few one versus all queries. In our empirical study we show that our
Adaptive quantization in minsum based irregular LDPC decoder
 in Proc. IEEE Int. Symp. on Circuits Syst
, 2009
"... Abstract—In this paper, we present adaptive quantization schemes in the normalized minsum decoding algorithm considering scaling effects to improve the performance of irregular lowdensity paritycheck (LDPC) decoder for WirelessMAN (IEEE 802.16e) applications. We discuss the finite precision effec ..."
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Cited by 4 (2 self)
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Abstract—In this paper, we present adaptive quantization schemes in the normalized minsum decoding algorithm considering scaling effects to improve the performance of irregular lowdensity paritycheck (LDPC) decoder for WirelessMAN (IEEE 802.16e) applications. We discuss the finite precision
Results 1  10
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