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Finding Optimal Triangulations Via Minimal Vertex Separators
, 1997
"... An algorithm called QuickTree is developed for finding a triangulation T of a given undirected graph G such that the size of T 's maximal clique is minimum and such that no other triangulation of G is a subgraph of T . We have tested QuickTree on random graphs of up to 100 nodes for which the m ..."
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Cited by 1 (0 self)
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An algorithm called QuickTree is developed for finding a triangulation T of a given undirected graph G such that the size of T 's maximal clique is minimum and such that no other triangulation of G is a subgraph of T . We have tested QuickTree on random graphs of up to 100 nodes for which the maximum clique in an optimal triangulation is of size 11. This is the first algorithm that can optimally triangulate graphs of such size in a reasonable time frame. This algorithm is useful for constraint satisfaction problems and for Bayesian inference through the clique tree inference algorithm. 1 Introduction An undirected graph is triangulated (chordal) if for every cycle C of length greater than 3 the graph contains a chord, that is, an edge which connects two non adjacent vertices of C. Given an undirected graph G, a supergraph of G which is triangulated is called a triangulation of G. The problem we address is to find a triangulation T of G such that size of its maximal clique is minimum ...
A new learning algorithm for blind signal separation

, 1996
"... A new online learning algorithm which minimizes a statistical dependency among outputs is derived for blind separation of mixed signals. The dependency is measured by the average mutual information (MI) of the outputs. The source signals and the mixing matrix are unknown except for the number of ..."
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Cited by 622 (80 self)
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A new online learning algorithm which minimizes a statistical dependency among outputs is derived for blind separation of mixed signals. The dependency is measured by the average mutual information (MI) of the outputs. The source signals and the mixing matrix are unknown except for the number
A Separator Theorem for Planar Graphs
, 1977
"... Let G be any nvertex planar graph. We prove that the vertices of G can be partitioned into three sets A, B, C such that no edge joins a vertex in A with a vertex in B, neither A nor B contains more than 2n/3 vertices, and C contains no more than 2& & vertices. We exhibit an algorithm which ..."
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Cited by 461 (1 self)
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Let G be any nvertex planar graph. We prove that the vertices of G can be partitioned into three sets A, B, C such that no edge joins a vertex in A with a vertex in B, neither A nor B contains more than 2n/3 vertices, and C contains no more than 2& & vertices. We exhibit an algorithm which
A tutorial on support vector machines for pattern recognition
 Data Mining and Knowledge Discovery
, 1998
"... The tutorial starts with an overview of the concepts of VC dimension and structural risk minimization. We then describe linear Support Vector Machines (SVMs) for separable and nonseparable data, working through a nontrivial example in detail. We describe a mechanical analogy, and discuss when SV ..."
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Cited by 3393 (12 self)
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The tutorial starts with an overview of the concepts of VC dimension and structural risk minimization. We then describe linear Support Vector Machines (SVMs) for separable and nonseparable data, working through a nontrivial example in detail. We describe a mechanical analogy, and discuss when
Live Migration of Virtual Machines
 In Proceedings of the 2nd ACM/USENIX Symposium on Networked Systems Design and Implementation (NSDI
, 2005
"... Migrating operating system instances across distinct physical hosts is a useful tool for administrators of data centers and clusters: It allows a clean separation between hardware and software, and facilitates fault management, load balancing, and lowlevel system maintenance. By carrying out the ma ..."
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Cited by 636 (15 self)
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Migrating operating system instances across distinct physical hosts is a useful tool for administrators of data centers and clusters: It allows a clean separation between hardware and software, and facilitates fault management, load balancing, and lowlevel system maintenance. By carrying out
Diagnosing multiple faults.
 Artificial Intelligence,
, 1987
"... Abstract Diagnostic tasks require determining the differences between a model of an artifact and the artifact itself. The differences between the manifested behavior of the artifact and the predicted behavior of the model guide the search for the differences between the artifact and its model. The ..."
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Cited by 808 (62 self)
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in the domain of troubleshooting digital circuits. This research makes several novel contributions: First, the system diagnoses failures due to multiple faults. Second, failure candidates are represented and manipulated in terms of minimal sets of violated assumptions, resulting in an efficient diagnostic
Stacked generalization
 NEURAL NETWORKS
, 1992
"... This paper introduces stacked generalization, a scheme for minimizing the generalization error rate of one or more generalizers. Stacked generalization works by deducing the biases of the generalizer(s) with respect to a provided learning set. This deduction proceeds by generalizing in a second sp ..."
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Cited by 731 (9 self)
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This paper introduces stacked generalization, a scheme for minimizing the generalization error rate of one or more generalizers. Stacked generalization works by deducing the biases of the generalizer(s) with respect to a provided learning set. This deduction proceeds by generalizing in a second
ReTiling Polygonal Surfaces
 Computer Graphics
, 1992
"... This paper presents an automatic method of creating surface models at several levels of detail from an original polygonal description of a given object. Representing models at various levels of detail is important for achieving high frame rates in interactive graphics applications and also for speed ..."
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Cited by 445 (3 self)
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model and the new points that are to become vertices in the retiled surface. The new model is then created by removing each original vertex and locally retriangulating the surface in a way that matches the local connectedness of the initial surface. This technique for surface retessellation has been
Sparse Reconstruction by Separable Approximation
, 2007
"... Finding sparse approximate solutions to large underdetermined linear systems of equations is a common problem in signal/image processing and statistics. Basis pursuit, the least absolute shrinkage and selection operator (LASSO), waveletbased deconvolution and reconstruction, and compressed sensing ..."
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Cited by 373 (38 self)
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of minimizing the sum of a smooth convex function and a nonsmooth, possibly nonconvex, sparsityinducing function. We propose iterative methods in which each step is an optimization subproblem involving a separable quadratic term (diagonal Hessian) plus the original sparsityinducing term. Our approach
Online selection of discriminative tracking features
, 2003
"... This paper presents an online feature selection mechanism for evaluating multiple features while tracking and adjusting the set of features used to improve tracking performance. Our hypothesis is that the features that best discriminate between object and background are also best for tracking the ..."
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Cited by 356 (5 self)
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according to how well they separate sample distributions of object and background pixels. This feature evaluation mechanism is embedded in a meanshift tracking system that adaptively selects the topranked discriminative features for tracking. Examples are presented that demonstrate how this method adapts
Results 1  10
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