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GRAPH LAPLACIAN FOR INTERACTIVE IMAGE RETRIEVAL
"... Interactive image search or relevance feedback is the process which helps a user refining his query and finding difficult target categories. This consists in a stepbystep labeling of a very small fraction of an image database and iteratively refining a decision rule using both the labeled and unla ..."
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Cited by 3 (2 self)
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and unlabeled data. Training of this decision rule is referred to as transductive learning. Our work is an original approach for relevance feedback based on Graph Laplacian. We introduce a new Graph Laplacian which makes it possible to robustly learn the embedding of the manifold enclosing the dataset via a
Graph Laplacians and Stabilization of Vehicle Formations
, 2001
"... Control of vehicle formations has emerged as a topic of significant interest to the controls community. In this paper, we merge tools from graph theory and control theory to derive stability criteria for formation stabilization. The interconnection between vehicles (i.e., which vehicles are sensed b ..."
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Cited by 95 (7 self)
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by other vehicles) is modeled as a graph, and the eigenvalues of the Laplacian matrix of the graph are used in stating a Nyquistlike stability criterion for vehicle formations. The location of the Laplacian eigenvalues can be correlated to the graph structure, and therefore used to identify desirable
Graph laplacians and their convergence on random neighborhood graphs
 Journal of Machine Learning Research
, 2006
"... Given a sample from a probability measure with support on a submanifold in Euclidean space one can construct a neighborhood graph which can be seen as an approximation of the submanifold. The graph Laplacian of such a graph is used in several machine learning methods like semisupervised learning, d ..."
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Cited by 36 (7 self)
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Given a sample from a probability measure with support on a submanifold in Euclidean space one can construct a neighborhood graph which can be seen as an approximation of the submanifold. The graph Laplacian of such a graph is used in several machine learning methods like semisupervised learning
Motion Deblurring With Graph Laplacian Regularization
"... In this paper, we develop a regularization framework for image deblurring based on a new definition of the normalized graph Laplacian. We apply a fast scaling algorithm to the kernel similarity matrix to derive the symmetric, doubly stochastic filtering matrix from which the normalized Laplacian mat ..."
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In this paper, we develop a regularization framework for image deblurring based on a new definition of the normalized graph Laplacian. We apply a fast scaling algorithm to the kernel similarity matrix to derive the symmetric, doubly stochastic filtering matrix from which the normalized Laplacian
Accelerated multigrid for graph Laplacian operators
, 2015
"... We consider multigrid type techniques for the numerical solution of large linear systems, whose coefficient matrices show the structure of (weighted) graph Laplacian operators. We combine ad hoc coarsergrid operators with iterative techniques used as smoothers. Empirical tests suggest that the most ..."
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We consider multigrid type techniques for the numerical solution of large linear systems, whose coefficient matrices show the structure of (weighted) graph Laplacian operators. We combine ad hoc coarsergrid operators with iterative techniques used as smoothers. Empirical tests suggest
Convex optimization of graph Laplacian eigenvalues
 in International Congress of Mathematicians
"... Abstract. We consider the problem of choosing the edge weights of an undirected graph so as to maximize or minimize some function of the eigenvalues of the associated Laplacian matrix, subject to some constraints on the weights, such as nonnegativity, or a given total value. In many interesting case ..."
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Cited by 50 (0 self)
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Abstract. We consider the problem of choosing the edge weights of an undirected graph so as to maximize or minimize some function of the eigenvalues of the associated Laplacian matrix, subject to some constraints on the weights, such as nonnegativity, or a given total value. In many interesting
Graph Laplacians and Least Squares on Graphs
"... Abstract—There are several classes of operators on graphs to consider in deciding on a collection of building blocks for graph algorithms. One class involves traditional graph operations such as breadth first or depth first search, finding connected components, spanning trees, cliques and other subg ..."
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Abstract—There are several classes of operators on graphs to consider in deciding on a collection of building blocks for graph algorithms. One class involves traditional graph operations such as breadth first or depth first search, finding connected components, spanning trees, cliques and other
Large mesh deformation using the volumetric graph Laplacian
 ACM Transactions on Graphics
"... We present a novel technique for large deformations on 3D meshes using the volumetric graph Laplacian. We first construct a graph representing the volume inside the input mesh. The graph need not form a solid meshing of the input mesh’s interior; its edges simply connect nearby points in the volume. ..."
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Cited by 92 (13 self)
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We present a novel technique for large deformations on 3D meshes using the volumetric graph Laplacian. We first construct a graph representing the volume inside the input mesh. The graph need not form a solid meshing of the input mesh’s interior; its edges simply connect nearby points in the volume
Results 11  20
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33,626