Results 211 to 220 of about 76,384 (242)
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Graph Embeddings and Laplacian Eigenvalues
SIAM Journal on Matrix Analysis and Applications, 2000Summary: Graph embeddings are useful in bounding the smallest nontrivial eigenvalues of Laplacian matrices from below. For an \(n \times n\) Laplacian, these embedding methods can be characterized as follows: The lower bound is based on a clique embedding into the underlying graph of the Laplacian. An embedding can be represented by a matrix \(\Gamma\);
Guattery, Stephen, Miller, Gary L.
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GRAPHS CHARACTERIZED BY LAPLACIAN EIGENVALUES
Chinese Annals of Mathematics, 2004zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Laplacian Eigenvectors of Graphs
2007[No abstract available] Publisher's ...
Türker Biyikoğu +2 more
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Deformed Graph Laplacian for Semisupervised Learning
IEEE Transactions on Neural Networks and Learning Systems, 2015Graph Laplacian has been widely exploited in traditional graph-based semisupervised learning (SSL) algorithms to regulate the labels of examples that vary smoothly on the graph. Although it achieves a promising performance in both transductive and inductive learning, it is not effective for handling ambiguous examples (shown in Fig. 1).
Chen, Gong +5 more
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Integrative oncology: Addressing the global challenges of cancer prevention and treatment
Ca-A Cancer Journal for Clinicians, 2022Jun J Mao,, Msce +2 more
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Graphs and Associated Laplacians
2012In this chapter, we provide the necessary notation and basic results on spectral graph theory needed in the subsequent chapters. Results on spectral theory of combinatorial Laplacians can be found e.g. in [Do84, MW89, CdV98, CGY96, Chu97, HS99, Sh00, HS04, Su08].
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Multidisciplinary standards of care and recent progress in pancreatic ductal adenocarcinoma
Ca-A Cancer Journal for Clinicians, 2020Aaron J Grossberg +2 more
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