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8,491
Simple fast algorithms for the editing distance between trees and related problems
 SIAM J. COMPUT
, 1989
"... Ordered labeled trees are trees in which the lefttoright order among siblings is. significant. The distance between two ordered trees is considered to be the weighted number of edit operations (insert, delete, and modify) to transform one tree to another. The problem of approximate tree matching i ..."
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Cited by 405 (12 self)
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is also considered. Specifically, algorithms are designed to answer the following kinds of questions: 1. What is the distance between two trees? 2. What is the minimum distance between T and T when zero or more subtrees can be removed from T2 3. Let the pruning of a tree at node n mean removing all
Shape matching and object recognition using low distortion correspondence
 In CVPR
, 2005
"... We approach recognition in the framework of deformable shape matching, relying on a new algorithm for finding correspondences between feature points. This algorithm sets up correspondence as an integer quadratic programming problem, where the cost function has terms based on similarity of correspond ..."
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Cited by 419 (15 self)
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We approach recognition in the framework of deformable shape matching, relying on a new algorithm for finding correspondences between feature points. This algorithm sets up correspondence as an integer quadratic programming problem, where the cost function has terms based on similarity
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
Learning String Edit Distance
, 1997
"... In many applications, it is necessary to determine the similarity of two strings. A widelyused notion of string similarity is the edit distance: the minimum number of insertions, deletions, and substitutions required to transform one string into the other. In this report, we provide a stochastic mo ..."
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Cited by 252 (2 self)
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In many applications, it is necessary to determine the similarity of two strings. A widelyused notion of string similarity is the edit distance: the minimum number of insertions, deletions, and substitutions required to transform one string into the other. In this report, we provide a stochastic
Estimating dynamic models of imperfect competition
, 2007
"... We describe a twostep algorithm for estimating dynamic games under the assumption that behavior is consistent with Markov perfect equilibrium. In the first step, the policy functions and the law of motion for the state variables are estimated. In the second step, the remaining structural parameters ..."
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Cited by 279 (14 self)
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parameters are estimated using the optimality conditions for equilibrium. The second step estimator is a simple simulated minimum distance estimator. The algorithm applies to a broad class of models, including industry competition models with both discrete and continuous controls such as the Ericson
On constructing minimum spanning trees in kdimensional space and related problems
 SIAM JOURNAL ON COMPUTING
, 1982
"... . The problem of finding a minimum spanning tree connecting n points in a kdimensional space is discussed under three common distance metrics: Euclidean, rectilinear, and L. By employing a subroutine that solves the post office problem, we show that, for fixed k _> 3, such a minimum spanning t ..."
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Cited by 222 (1 self)
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. The problem of finding a minimum spanning tree connecting n points in a kdimensional space is discussed under three common distance metrics: Euclidean, rectilinear, and L. By employing a subroutine that solves the post office problem, we show that, for fixed k _> 3, such a minimum spanning
Coding for errors and erasures in random network coding
, 2007
"... The problem of errorcontrol in random network coding is considered. A “noncoherent” or “channel oblivious ” model is assumed where neither transmitter nor receiver is assumed to have knowledge of the channel transfer characteristic. Motivated by the property that random network coding is vectorspa ..."
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Cited by 260 (14 self)
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space preserving, information transmission is modelled as the injection into the network of a basis for a vector space V and the collection by the receiver of a basis for a vector space U. We introduce a metric on the space of all subspaces of a fixed vector space, and show that a minimum distance decoder
Learning a distance metric from relative comparisons
 In Proc. Advances in Neural Information Processing Systems
, 2003
"... This paper presents a method for learning a distance metric from relative comparison such as “A is closer to B than A is to C”. Taking a Support Vector Machine (SVM) approach, we develop an algorithm that provides a flexible way of describing qualitative training data as a set of constraints. We sh ..."
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Cited by 195 (0 self)
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This paper presents a method for learning a distance metric from relative comparison such as “A is closer to B than A is to C”. Taking a Support Vector Machine (SVM) approach, we develop an algorithm that provides a flexible way of describing qualitative training data as a set of constraints. We
Distance transforms of sampled functions
 Cornell Computing and Information Science
, 2004
"... This paper provides lineartime algorithms for solving a class of minimization problems involving a cost function with both local and spatial terms. These problems can be viewed as a generalization of classical distance transforms of binary images, where the binary image is replaced by an arbitrary ..."
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Cited by 175 (9 self)
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by an arbitrary sampled function. Alternatively they can be viewed in terms of the minimum convolution of two functions, which is an important operation in grayscale morphology. A useful consequence of our techniques is a simple, fast method for computing the Euclidean distance transform of a binary image
Efficiency of the minimum quadratic distance estimator for the bivariate Poisson distribution
, 2009
"... To cite this version: ..."
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