Results 51 to 60 of about 178,314 (358)
Large graph clustering using DCT-based graph clustering [PDF]
2014 IEEE Symposium on Computational Intelligence in Big Data (CIBD), 2014 With the proliferation of the World Wide Web, graph structures have arisen on social network/media sites. Such graphs usually number several million nodes, i.e., they can be characterized as Big Data. Graph clustering is an important analysis tool for other graph related tasks, such as compression, community discovery and recommendation systems, to ...
Nikolaos Tsapanos +3 more
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Cluster graph modification problems [PDF]
Discrete Applied Mathematics, 2002 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ron Shamir, Roded Sharan, Dekel Tsur
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Randomized graph cluster randomization
Journal of Causal Inference, 2023 Abstract The global average treatment effect (GATE) is a primary quantity of interest in the study of causal inference under network interference. With a correctly specified exposure model of the interference, the Horvitz–Thompson (HT) and Hájek estimators of the GATE are unbiased and consistent, respectively, yet
Ugander Johan, Yin Hao
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A survey of two-dimensional graph layout techniques for information visualisation [PDF]
, 2012 Many algorithms for graph layout have been devised over the last 30 years spanning both the graph drawing and information visualisation communities. This article first reviews the advances made in the field of graph drawing that have then often been ...
Vickers, Paul, Gibson, Helen, Faith, Joe
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Three-Way Decision-Driven Adaptive Graph Convolution for Deep Clustering
Applied SciencesGraph clustering is an efficient method for deep clustering that utilizes graph convolution. Graph convolution effectively combines structure and content information, and lots of recent graph convolution-based methods have shown promising results in ...
Wei Liang +4 more
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FEBS Letters, EarlyView.In this study, we found that human cervical‐derived adipocytes maintain intracellular iron level by regulating the expression of iron transport‐related proteins during adrenergic stimulation. Melanotransferrin is predicted to interact with transferrin receptor 1 based on in silico analysis.
Rahaf Alrifai +9 more
wiley +1 more source
Replicator Graph Clustering [PDF]
Procedings of the British Machine Vision Conference 2013, 2013 In this paper we introduce an efficient, effective and scalable clustering method denoted as Replicator Graph Clustering. Our method takes measures of similarity between pairs of data points (i. e. an affinity matrix) as input and identifies a set of clusters and unique cluster assignments in a fully unsupervised manner, where the cluster granularity ...
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A parameter-free graph reduction for spectral clustering and SpectralNet
Array, 2022 Graph-based clustering methods like spectral clustering and SpectralNet are very efficient in detecting clusters of non-convex shapes. Unlike the popular k-means, graph-based clustering methods do not assume that each cluster has a single mean.
Mashaan Alshammari +2 more
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Tau acetylation at K331 has limited impact on tau pathology in vivo
FEBS Letters, EarlyView.We mapped tau post‐translational modifications in humanized MAPT knock‐in mice and in amyloid‐bearing double knock‐in mice. Acetylation within the repeat domain, particularly around K331, showed modest increases under amyloid pathology. To test functional relevance, we generated MAPTK331Q knock‐in mice.
Shoko Hashimoto +3 more
wiley +1 more source
Central Clustering of Attributed Graphs [PDF]
Machine Learning, 2004 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Brijnesh J. Jain, Fritz Wysotzki
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