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The iterated version space algorithm
 In Proc. of Ninth Florida Arti cial IntelligenceResearch Symposium (FLAIRS96
, 1996
"... We present the Iterated Version Space Algorithm (IVSA), which retains many advantages of the Version Space Algorithm while handling disjunctive concepts and noise. IVSA repeatedly generates hypotheses for regions of the concept space and combines these regional hypotheses to produce an overall conce ..."
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Cited by 1 (1 self)
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We present the Iterated Version Space Algorithm (IVSA), which retains many advantages of the Version Space Algorithm while handling disjunctive concepts and noise. IVSA repeatedly generates hypotheses for regions of the concept space and combines these regional hypotheses to produce an overall
Learning English Grapheme Segmentation Using the Iterated Version Space Algorithm
 in the International Symposium on Methodologies for Intelligent Systems
"... Abstract. Our unique approach for learning English grapheme segmentation (LEGS) rules using the Iterated Version Space Algorithm (IVSA) is presented. After de ning the problem and our representation for the instances and hypotheses, we illustrate the LEGS approach by tracing a speci c example. Exp ..."
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Abstract. Our unique approach for learning English grapheme segmentation (LEGS) rules using the Iterated Version Space Algorithm (IVSA) is presented. After de ning the problem and our representation for the instances and hypotheses, we illustrate the LEGS approach by tracing a speci c example
Depthfirst IterativeDeepening: An Optimal Admissible Tree Search
 Artificial Intelligence
, 1985
"... The complexities of various search algorithms are considered in terms of time, space, and cost of solution path. It is known that breadthfirst search requires too much space and depthfirst search can use too much time and doesn't always find a cheapest path. A depthfirst iteratiwdeepening a ..."
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Cited by 517 (23 self)
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The complexities of various search algorithms are considered in terms of time, space, and cost of solution path. It is known that breadthfirst search requires too much space and depthfirst search can use too much time and doesn't always find a cheapest path. A depthfirst iteratiw
"GrabCut”  interactive foreground extraction using iterated graph cuts
 ACM TRANS. GRAPH
, 2004
"... The problem of efficient, interactive foreground/background segmentation in still images is of great practical importance in image editing. Classical image segmentation tools use either texture (colour) information, e.g. Magic Wand, or edge (contrast) information, e.g. Intelligent Scissors. Recently ..."
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Cited by 1122 (36 self)
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. Recently, an approach based on optimization by graphcut has been developed which successfully combines both types of information. In this paper we extend the graphcut approach in three respects. First, we have developed a more powerful, iterative version of the optimisation. Secondly, the power
The algorithmic analysis of hybrid systems
 THEORETICAL COMPUTER SCIENCE
, 1995
"... We present a general framework for the formal specification and algorithmic analysis of hybrid systems. A hybrid system consists of a discrete program with an analog environment. We model hybrid systems as nite automata equipped with variables that evolve continuously with time according to dynamica ..."
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Cited by 771 (71 self)
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to linear hybrid systems. In particular, we consider symbolic modelchecking and minimization procedures that are based on the reachability analysis of an infinite state space. The procedures iteratively compute state sets that are definable as unions of convex polyhedra in multidimensional real space. We
Data Streams: Algorithms and Applications
, 2005
"... In the data stream scenario, input arrives very rapidly and there is limited memory to store the input. Algorithms have to work with one or few passes over the data, space less than linear in the input size or time significantly less than the input size. In the past few years, a new theory has emerg ..."
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Cited by 528 (22 self)
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In the data stream scenario, input arrives very rapidly and there is limited memory to store the input. Algorithms have to work with one or few passes over the data, space less than linear in the input size or time significantly less than the input size. In the past few years, a new theory has
Efficient Variants of the ICP Algorithm
 INTERNATIONAL CONFERENCE ON 3D DIGITAL IMAGING AND MODELING
, 2001
"... The ICP (Iterative Closest Point) algorithm is widely used for geometric alignment of threedimensional models when an initial estimate of the relative pose is known. Many variants of ICP have been proposed, affecting all phases of the algorithm from the selection and matching of points to the minim ..."
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Cited by 702 (5 self)
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The ICP (Iterative Closest Point) algorithm is widely used for geometric alignment of threedimensional models when an initial estimate of the relative pose is known. Many variants of ICP have been proposed, affecting all phases of the algorithm from the selection and matching of points
The Iterated Version Space Learning
"... Abstract. Inspired with Version Space learning, the Iterated Version Space Algorithm (IVSA) has been designed and implemented to learn disjunctive concepts. IVSA dynamically partitions its search space of potential hypotheses of the target concept into contourshaped regions until all training insta ..."
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Abstract. Inspired with Version Space learning, the Iterated Version Space Algorithm (IVSA) has been designed and implemented to learn disjunctive concepts. IVSA dynamically partitions its search space of potential hypotheses of the target concept into contourshaped regions until all training
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 536 (21 self)
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toimplement algorithm that is extremely efficient at addressing problems in which the optimal solution has low rank. The algorithm is iterative and produces a sequence of matrices {X k, Y k} and at each step, mainly performs a softthresholding operation on the singular values of the matrix Y k. There are two
Depth first search and linear graph algorithms
 SIAM JOURNAL ON COMPUTING
, 1972
"... The value of depthfirst search or "backtracking" as a technique for solving problems is illustrated by two examples. An improved version of an algorithm for finding the strongly connected components of a directed graph and ar algorithm for finding the biconnected components of an undirect ..."
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Cited by 1380 (19 self)
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The value of depthfirst search or "backtracking" as a technique for solving problems is illustrated by two examples. An improved version of an algorithm for finding the strongly connected components of a directed graph and ar algorithm for finding the biconnected components
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