The Incompatibility graph and Dobrushin’s approximation
Auto-Approximation of Graph Computing
... era, graph computing is one of the challenging issues because there are numerous large graph datasets emerging from real ...large graph? When it is impossible to know the exact answer in a limited ...
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PTB Graph Parsing with Tree Approximation
... PTB graph-structured represen- tations by trees. By our approximation method, we can reduce nonlocal dependency identification and constituency parsing into single tree-based ...our approximation ...
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Approximation algorithms for submodular optimization and graph problems
... Chapter 1 Introduction This thesis considers several discrete optimization problems. At a high level, these problems can be divided into two broad classes. The first class consists of problems involving submodular ...
201
Approximation algorithms for some graph partitioning problems
... Since the maximum (minimum) orthogonal partition problem and the max- imum (minimum) clique problem are all NP-complete, it is worthwhile to find approximation algorithms for these problems, and this is the goal ...
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Approximation Algorithms for Connected Graph Factor Problems
... could for instance be useful in real world problems where one wants to create a connected graph and some vertices are to have a degree of one. For this case one can use algorithm Algorithm 4, but there will be ...
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Efficient Tree based Approximation for Entailment Graph Learning
... of graph termed forest-reducible ...the graph edges, where each iteration takes linear ...our approximation algorithm to a recently-proposed state-of-the-art exact algo- rithm and show that it is ...
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The SMC′ Is a Highly Accurate Approximation to the Ancestral Recombination Graph
... *Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts 02138, † Department of Computer Science, Columbia University, New York, New York 10027, and ‡ Bioinformatics Research ...
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Novel Approximation Algorithm for Calculating Maximum Flow in a Graph
... new approximation algorithm for calculating the min-cut tree of an undirected edge- weighted graph has been ...given graph and d is the degree of the ...
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A Combinatorial Approximation Algorithm for Graph Balancing with Light Hyper Edges
... Due to the space limit, some of the proofs are omitted. Please refer to the full version [7] for details. Related Work For restricted assignment, besides the several recent advances mentioned earlier, see the survey of ...
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Heuristic Algorithm for Approximation Betweenness Centrality Using Graph Coarsening
... Nowadays, graph analytics are widely used in many research fields and ...on graph coarsening for approximating values of betweenness centrality, when new edges are ...
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A max-cut approximation using a graph based MBO scheme
... such graph problems has gained ...the graph problem are transcribed from their usual continuum formulation to a graph based ...the graph Ginzburg–Landau functional, which was introduced in [ ...
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Quantum Speedup for Graph Sparsification, Cut Approximation and Laplacian Solving
... -cut sparsifier must contain a constant fraction of the edges. As such, the constructed graphs are in fact already sparsifiers. We then carefully “hide” these sparsifiers in a larger, denser graph, in such a way ...
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metric space, approximation algorithm, linear programming relaxation, graph
... PROBLEM GRUIA CALINESCU ∗ , HOWARD KARLOFF † , AND YUVAL RABANI ‡ Abstract. In the 0-extension problem, we are given a weighted graph with some nodes marked as terminals and a semimetric on the set of terminals. ...
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Graph Connectivity: Approximation Algorithms and Applications to Protein-Protein Interaction Networks
... complex graph with another graph of the same degree distribution, when what we really want is to compare it to other graphs from the Y2H ...“matched” graph that we call a ...final graph more ...
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Eight Friends Are Enough: Social Graph Approximation via Public Listings
... computing graph statis- tics given a random sample of k edges from each node, and found that many interesting properties can be accurately ...leaking graph information enables transitive privacy loss: ...
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Sublinear time approximation of the cost of a metric k-nearest neighbor graph
... fundamental graph structure. As already described above, computing a k-NN graph requires some distance or similarity ...k-NN graph in such a general setting requires quadratic time, we will consider ...
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Poisson approximation of induced subgraph counts in an inhomogeneous random intersection graph model
... bipartite graph B(n, m, F, f n ) with vertex sets V and W is constructed by joining v i ∈ V and w ∈ W (denoted v i ∼ w) independently in such way that p i := P(v i ∼ w) = f n (θ i ...intersection graph G(n, ...
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Decision and approximation complexity for identifying codes and locating-dominating sets in restricted graph classes
... The abbreviations “NP-h”, “APX-h”, “log-APX-h”, “DSP” and “AT-free” stand for “NP-hard”, “APX-hard”, “log-APX-hard”, “Dominating Shortest Path” and “asteroidal triple-free”, respectively. Definitions of graph ...
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Nonparametric Density Estimation on A Graph: Learning Framework, Fast Approximation and Application in Image Segmentation
... adjacency graph and in addition, further improves the smoothing and segmen- tation ...adjacency graph where edges corresponds to the eight-connectivities of two regions and edge weights are defined as the ...
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Multi-hop Graph Convolutional Network with High-order Chebyshev Approximation for Text Reasoning
... tasks. Graph Trans- former (Dwivedi and Bresson, 2020) generalizes the Transformer to arbitrary graphs, and improves inductive learning from Laplacian eigenvectors on graph ...fully-connected graph ...
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