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LinearTime Algorithms in Memory Hierarchies
"... This paper studies lineartime algorithms on a hierarchical memory model called Block Move (BM), which extends the Block Transfer (BT) model of Aggarwal, Chandra, and Snir, and which is more stringent than a pipelining model studied recently by Luccio and Pagli. Upper and lower bounds are shown for ..."
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Cited by 2 (1 self)
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This paper studies lineartime algorithms on a hierarchical memory model called Block Move (BM), which extends the Block Transfer (BT) model of Aggarwal, Chandra, and Snir, and which is more stringent than a pipelining model studied recently by Luccio and Pagli. Upper and lower bounds are shown
On lineartime algorithms for fivecoloring planar graphs
 Inform. Process. Lett
, 1984
"... Certain properties of planar graphs are established in a particularly straightforward fashion. These properties assure good performance in two lineartime algorithms for fivecoloring planar graphs. A new lineartime algorithm, based on a third property, is also presented. Keywords: Graph coloring, ..."
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Cited by 4 (0 self)
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Certain properties of planar graphs are established in a particularly straightforward fashion. These properties assure good performance in two lineartime algorithms for fivecoloring planar graphs. A new lineartime algorithm, based on a third property, is also presented. Keywords: Graph coloring
LinearTime Algorithms for the Multiple Gene Duplication Problems
 IEEE Trans. Computational Biology and Bioinformatics
, 2011
"... Abstract—A fundamental problem arising in the evolutionary molecular biology is to discover the locations of gene duplications and multiple gene duplication episodes based on the phylogenetic information. The solutions to the MULTIPLE GENE DUPLICATION problems can provide useful clues to place the g ..."
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Cited by 5 (0 self)
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the results of Burleigh et al. with an optimal lineartime algorithm. For the ME problem, on the basis of the algorithm presented by Bansal and Eulenstein, we propose an optimal lineartime algorithm. Index Terms—Computational phylogenetics, gene duplication, computations on discrete structures, lineartime
Linear Time Algorithms Based on . . .
, 2008
"... In this paper I present general outlook on questions relevant to the basic graph algorithms; Finding the Shortest Path with Positive Weights and Minimum Spanning Tree. I will show so far known solution set of basic graph problems and present my own. My solutions to graph problems are characterized b ..."
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by their linear worstcase time complexity. It should be noticed that the algorithms which compute the Shortest Path and Minimum Spanning Tree problems not only analyze the weight of arcs (which is the main and often the only criterion of solution hitherto known algorithms) but also in case of identical path
Linear time algorithms for Clobber
, 2007
"... We prove that the singleplayer game clobber is solvable in linear time when played on a line or on a cycle. For this purpose, we show that this game is equivalent to an optimization problem on a set of words defined by seven classes of forbidden patterns. We also prove that, playing on the cycle, i ..."
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We prove that the singleplayer game clobber is solvable in linear time when played on a line or on a cycle. For this purpose, we show that this game is equivalent to an optimization problem on a set of words defined by seven classes of forbidden patterns. We also prove that, playing on the cycle
A Lineartime Algorithm for Sparsification . . .
"... Given an undirected graph G and an error parameter ε> 0, the graph sparsification problem requires sampling edges in G and giving the sampled edges appropriate weights to obtain a sparse graph Gε with the following property: the weight of every cut in Gε is within a factor of (1 ± ε) of the weigh ..."
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) of the weight of the corresponding cut in G. If G is unweighted, an O(mlogn)time algorithm for constructing Gε with O(nlogn/ε²) edges in expectation, and an O(m)time algorithm for constructing Gε with O(nlog² n/ε²) edges in expectation have recently been developed [9]. In this paper, we improve these results
Constructive Linear Time Algorithms for Branchwidth
, 1997
"... We prove that, for any fixed k, one can construct a linear time algorithm that checks if a graph has branchwidth k and, if so, outputs a branch decomposition of minimum width. 1 Introduction This paper considers the problem of finding branch decompositions of graphs with small branchwidth. The noti ..."
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Cited by 33 (7 self)
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We prove that, for any fixed k, one can construct a linear time algorithm that checks if a graph has branchwidth k and, if so, outputs a branch decomposition of minimum width. 1 Introduction This paper considers the problem of finding branch decompositions of graphs with small branchwidth
A Simple Linear Time Algorithm for . . .
"... A circulararc model M = (C, A) is a circle C together with a collection A of arcs of C. If no arc is contained in any other then M is a proper circulararc model, and if some point of C is not covered by any arc then M is an interval model. A (proper) (interval) circulararc graph is the intersecti ..."
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is the intersection graph of a (proper) (interval) circulararc model. Circulararc graphs and their subclasses have been the object of a great deal of attention in the literature. Linear time recognition algorithms have been described both for the general class and for some of its subclasses. For the isomorphism
A linear time algorithm for approximate . . .
, 2005
"... Matousek [Discrete Comput. Geom. 24 (1) (2000) 61–84] designed an O(nlog n) deterministic algorithm for the approximate 2means clustering problem for points in fixed dimensional Euclidean space which had left open the possibility of a linear time algorithm. In this paper, we present a simple random ..."
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Matousek [Discrete Comput. Geom. 24 (1) (2000) 61–84] designed an O(nlog n) deterministic algorithm for the approximate 2means clustering problem for points in fixed dimensional Euclidean space which had left open the possibility of a linear time algorithm. In this paper, we present a simple
A Randomized LinearTime Algorithm to Find Minimum Spanning Trees
, 1994
"... We present a randomized lineartime algorithm to find a minimum spanning tree in a connected graph with edge weights. The algorithm uses random sampling in combination with a recently discovered lineartime algorithm for verifying a minimum spanning tree. Our computational model is a unitcost ra ..."
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Cited by 136 (6 self)
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We present a randomized lineartime algorithm to find a minimum spanning tree in a connected graph with edge weights. The algorithm uses random sampling in combination with a recently discovered lineartime algorithm for verifying a minimum spanning tree. Our computational model is a unit
Results 1  10
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