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Fig. 1: A sketch of a small network displaying community structure, with three groups of nodes with dense internal connections and sparser connections between groups.. In the study of networks, such as computer and information networks, social networks and biological networks, a number of different characteristics have been found to occur commonly, including the small-world property, heavy ...
fold phase (line 20–23): based on the local vertices in next frontier, send messages to owner processors of these vertices in processor-row. (line 25–28): merge all receiving messages and update the distance value of vertices in the next frontier. The pseudo-code below describes more details of 2D BFS algorithm, which comes from the paper: [5]
An example of a roofline model with added bandwidth ceilings. In this model, the two additional ceilings represent the absence of software prefetching and NUMA organization of memory . An example roofline model with added in-core ceilings , where the two added ceilings represent the lack of instruction level parallelism and task level parallelism .
In computer science, a graph is an abstract data type that is meant to implement the undirected graph and directed graph concepts from the field of graph theory within mathematics. A graph data structure consists of a finite (and possibly mutable) set of vertices (also called nodes or points ), together with a set of unordered pairs of these ...
However, Gerbner's model still suffers from many of the limitations of the earlier models it is based on. An example is the focus on the linear transmission of information without an in-depth discussion of the role of feedback loops. Another issue concerns the question of how meaning is created. [131] [134] [140]
A dashed line with an open arrow pointing away from the source to the target is used to represent information flow. The keyword "flow" may be written above or below the dashed line. Information items represent the abstraction of data and act as information flow connectors, representing the flow of transfer of information from source to target.
Geometric graph theory in the broader sense is a large and amorphous subfield of graph theory, concerned with graphs defined by geometric means. In a stricter sense, geometric graph theory studies combinatorial and geometric properties of geometric graphs, meaning graphs drawn in the Euclidean plane with possibly intersecting straight-line edges, and topological graphs, where the edges are ...
A graphical model or probabilistic graphical model (PGM) or structured probabilistic model is a probabilistic model for which a graph expresses the conditional dependence structure between random variables. Graphical models are commonly used in probability theory, statistics—particularly Bayesian statistics—and machine learning.