Results 41 to 50 of about 608,403 (284)
Connected Components in MapReduce and Beyond [PDF]
Proceedings of the ACM Symposium on Cloud Computing, 2014 Computing connected components of a graph lies at the core of many data mining algorithms, and is a fundamental subroutine in graph clustering. This problem is well studied, yet many of the algorithms with good theoretical guarantees perform poorly in practice, especially when faced with graphs with hundreds of billions of edges.
Raimondas Kiveris +4 more
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Component Order Edge Connectivity, Vertex Degrees, and Integer Partitions
Theory and Applications of GraphsGiven a finite, simple graph G, the k-component order connectivity (resp. edge connectivity) of G is the minimum number of vertices (resp. edges) whose removal results in a subgraph in which every component has an order of at most k − 1.
Michael R. Yatauro
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Electroencephalography (EEG)-Derived Markers to Measure Components of Attention Processing [PDF]
, 2017 Although extensively studied for decades, attention system remains an interesting challenge in neuroscience field. The Attention Network Task (ANT) has been developed to provide a measure of the efficiency for the three attention components ...
Anzolin, Alessandra +6 more
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Temporally connected components
Theoretical Computer SciencezbMATH Open Web Interface contents unavailable due to conflicting licenses.
Stefan Balev +2 more
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Connected Components Labeling on DRAGs [PDF]
2018 24th International Conference on Pattern Recognition (ICPR), 2018 In this paper we introduce a new Connected Components Labeling (CCL) algorithm which exploits a novel approach to model decision problems as Directed Acyclic Graphs with a root, which will be called Directed Rooted Acyclic Graphs (DRAGs). This structure supports the use of sets of equivalent actions, as required by CCL, and optimally leverages these ...
Bolelli, Federico +3 more
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Dynamics of random recurrent networks with correlated low-rank structure
Physical Review Research, 2020 A given neural network in the brain is involved in many different tasks. This implies that, when considering a specific task, the network's connectivity contains a component which is related to the task and another component which can be considered ...
Friedrich Schuessler +4 more
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, 2017 Recent studies on analyzing dynamic brain connectivity rely on sliding-window analysis or time-varying coefficient models which are unable to capture both smooth and abrupt changes simultaneously. Emerging evidence suggests state-related changes in brain
Ombao, Hernando +3 more
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Self-stabilizing Connected Components
2019 IEEE/ACM 9th Workshop on Fault Tolerance for HPC at eXtreme Scale (FTXS), 2019 For the problem of computing the connected components of a graph, this paper considers the design of algorithms that are resilient to transient hardware faults, like bit flips. More specifically, it applies the technique of \emph{self-stabilization}. A system is self-stabilizing if, when starting from a valid or invalid state, it is guaranteed to reach
Piyush Sao +4 more
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In situ molecular organization and heterogeneity of the Legionella Dot/Icm T4SS
FEBS Letters, EarlyView.We present a nearly complete in situ model of the Legionella Dot/Icm type IV secretion system, revealing its central secretion channel and identifying new components. Using cryo‐electron tomography with AI‐based modeling, our work highlights the structure, variability, and mechanism of this complex nanomachine, advancing understanding of bacterial ...
Przemysław Dutka +11 more
wiley +1 more source
Functional brain networks in schizophrenia: a review
Frontiers in Human Neuroscience, 2009 Functional magnetic resonance imaging (fMRI) has become a major technique for studying cognitive function and its disruption in mental illness, including schizophrenia.
Vince D Calhoun +6 more
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