Results 41 to 50 of about 156,516 (263)
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 Bibliometric Analysis of Publications in Uremic Toxins From 1991 to 2024
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Background Uremic toxins are a growing area of research in nephrology, with significant implications in the progression and treatment of chronic kidney disease (CKD) and the management of end‐stage kidney disease (ESKD). This bibliometric analysis aims to evaluate the global research trends, key contributors, and the impact of publications in ...
Yuh‐Shan Ho +7 more
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Sampling clustering based on multi-view attribute structural relations.
PLoS ONEIn light of the exponential growth in information volume, the significance of graph data has intensified. Graph clustering plays a pivotal role in graph data processing by jointly modeling the graph structure and node attributes.
Guoyang Tang +3 more
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Dynamic Graph Clustering Using Minimum-Cut Trees
Journal of Graph Algorithms and Applications, 2012 Algorithms or target functions for graph clustering rarely admit quality guarantees or optimal results in general. Based on properties of minimum-cut trees, a clustering algorithm by Flake et al.
Robert Görke +2 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
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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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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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FEBS Letters, EarlyView.This study reveals that the small GTPase Rab14 is necessary for human papillomavirus (HPV) infection and plays an essential role in the transport of virions to the trans‐Golgi network (TGN). HPV in the early endosome (EE), which harbors GTP‐bound Rab14, is transported to the TGN through the switch of Rab14 from its GTP‐bound to GDP‐bound form.
Yoshiyuki Ishii, Iwao Kukimoto
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One-step Multi-view Clustering Based on Diversity and Consistency [PDF]
Jisuanji gongchengWith the development of data collection technology, multi-view data have become increasingly common. Compared to single-view data, multi-view data contain richer information, which is usually characterized by consistency and diversity information.
HU Aoran, CHEN Xiaohong
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