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223,981
Random forests
 Machine Learning
, 2001
"... Abstract. Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. The generalization error for forests converges a.s. to a limit as the number of trees in the fo ..."
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Cited by 3433 (2 self)
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Abstract. Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. The generalization error for forests converges a.s. to a limit as the number of trees
SamplingTreeFragmentsfromForests
"... We study the problem of sampling trees from forests, in the setting where probabilities for each tree may be a function of arbitrarily large tree fragments. This setting extends recent work for samplingtolearnTreeSubstitutionGrammarstothecasewherethetreestructure(TSGderived tree) is not fixed. We de ..."
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We study the problem of sampling trees from forests, in the setting where probabilities for each tree may be a function of arbitrarily large tree fragments. This setting extends recent work for samplingtolearnTreeSubstitutionGrammarstothecasewherethetreestructure(TSGderived tree) is not fixed. We
HARVESTING SMALL TREES AND FOREST RESIDUES
"... Eight countries collaborated and shared technical information on the harvesting of small trees and forest residues in a three year program. Proceedings and reports from workshops and reviews are summarized in a review of activities and harvesting systems of the participating countries. Four database ..."
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Cited by 2 (0 self)
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Eight countries collaborated and shared technical information on the harvesting of small trees and forest residues in a three year program. Proceedings and reports from workshops and reviews are summarized in a review of activities and harvesting systems of the participating countries. Four
Tree and Forest Volumes of Graphs
, 2000
"... The tree volume of a weighted graph G is the “sum ” of the tree volumes of all spanning trees of G, and the tree volume of a weighted tree T is the product of the edge weights of T times the “product ” of the letters of the Prüfer code of T where the vertices of G are viewed as independent indeterm ..."
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Cited by 3 (0 self)
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indeterminants that can be multiplied and commute. The forest volume of G is the tree volume of the graph Gc obtained from G by adding a new vertex c and connecting every vertex of G with c by an arc of weight 1. We show that the forest volume is a natural generalization of the Laplacian polynomial of graphs
On computing the distinguishing numbers of trees and forests
 Electron. J. Combin
, 2006
"... Let G be a graph. A vertex labeling of G is distinguishing if the only labelpreserving automorphism of G is the identity map. The distinguishing number of G, D(G), isthe minimum number of labels needed so that G has a distinguishing labeling. In this paper, we present O(n log n)time algorithms tha ..."
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Cited by 12 (2 self)
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that compute the distinguishing numbers of trees and forests. Unlike most of the previous work in this area, our algorithm relies on the combinatorial properties of trees rather than their automorphism groups to compute for their distinguishing numbers. 1
Random directed trees and forest
, 2008
"... Consider the ddimensional lattice Zd where each vertex is `open ' or `closed ' with probability p or 1 p respectively. An open vertex v is connected by an edge to the closest open vertex w in the 45 (downward) light cone generated at v. In case of nonuniqueness of such a vertex w, we ..."
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choose any one of the closest vertices with equal probability and independently of the other random mechanisms. It is shown that this random graph is a tree almost surely for d = 2 and 3 and it is an innite collection of distinct trees for d 4. In addition, for any dimension, we show that there is no bi
SplitStream: HighBandwidth Multicast in Cooperative Environments
 SOSP '03
, 2003
"... In treebased multicast systems, a relatively small number of interior nodes carry the load of forwarding multicast messages. This works well when the interior nodes are highly available, d d cated infrastructure routers but it poses a problem for applicationlevel multicast in peertopeer systems. ..."
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Cited by 570 (17 self)
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. SplitStreamadV esses this problem by striping the content across a forest of interiornodno# sjoint multicast trees that d stributes the forward ng load among all participating peers. For example, it is possible to construct efficient SplitStream forests in which each peer contributes only as much
Selfadjusting binary search trees
, 1985
"... The splay tree, a selfadjusting form of binary search tree, is developed and analyzed. The binary search tree is a data structure for representing tables and lists so that accessing, inserting, and deleting items is easy. On an nnode splay tree, all the standard search tree operations have an am ..."
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Cited by 435 (19 self)
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The splay tree, a selfadjusting form of binary search tree, is developed and analyzed. The binary search tree is a data structure for representing tables and lists so that accessing, inserting, and deleting items is easy. On an nnode splay tree, all the standard search tree operations have
Implementing decision trees and forests on a GPU
 In Proceedings 10th European Conference on Computer Vision
, 2008
"... Abstract. We describe a method for implementing the evaluation and training of decision trees and forests entirely on a GPU, and show how this method can be used in the context of object recognition. Our strategy for evaluation involves mapping the data structure describing a decision forest to a 2 ..."
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Cited by 46 (2 self)
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Abstract. We describe a method for implementing the evaluation and training of decision trees and forests entirely on a GPU, and show how this method can be used in the context of object recognition. Our strategy for evaluation involves mapping the data structure describing a decision forest to a
A Framework for Dynamic Graph Drawing
 CONGRESSUS NUMERANTIUM
, 1992
"... Drawing graphs is an important problem that combines flavors of computational geometry and graph theory. Applications can be found in a variety of areas including circuit layout, network management, software engineering, and graphics. The main contributions of this paper can be summarized as follows ..."
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Cited by 627 (44 self)
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as follows: ffl We devise a model for dynamic graph algorithms, based on performing queries and updates on an implicit representation of the drawing, and we show its applications. ffl We present several efficient dynamic drawing algorithms for trees, seriesparallel digraphs, planar stdigraphs, and planar
Results 1  10
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