Lecture Slides
... called “moralization”). Lump variables in cliques together and form a tree of cliques—this may require a nasty step called “triangulation”. Do inference in this tree. Cutset Conditioning: or “reasoning by assumptions”. Find a small set of variables which, if they were given (i.e. known) would render ...
... called “moralization”). Lump variables in cliques together and form a tree of cliques—this may require a nasty step called “triangulation”. Do inference in this tree. Cutset Conditioning: or “reasoning by assumptions”. Find a small set of variables which, if they were given (i.e. known) would render ...
Planar Point Location - Brown Computer Science
... of the vertices of the embedded graph. Each slab consists of trapezoids created by the nonintersecting segments of the graph edges that pass through it. Finding the region containing a query point means identifying first the slab, then the trapezoid that contains it. The primary data structure is a ...
... of the vertices of the embedded graph. Each slab consists of trapezoids created by the nonintersecting segments of the graph edges that pass through it. Finding the region containing a query point means identifying first the slab, then the trapezoid that contains it. The primary data structure is a ...
GraphVisualization2 - Ohio State Computer Science and
... From successive application of clustering process Can be navigated as tree ...
... From successive application of clustering process Can be navigated as tree ...
Recitation Slides
... •Basis: trivial for n=1,2 , check for all trees with 3 nodes (there is only one such tree). •Assumption: correct for all trees of size n. •Step: prove for any tree of size n+1. Given such a tree, it must contain an internal node v. ...
... •Basis: trivial for n=1,2 , check for all trees with 3 nodes (there is only one such tree). •Assumption: correct for all trees of size n. •Step: prove for any tree of size n+1. Given such a tree, it must contain an internal node v. ...
Explicit construction of linear sized tolerant networks
... What is the minimum possible number of vertices and edges of a graph G, such that even after removing all but E portion of its vertices or edges, the remaining graph still contains a path of length m? This problem arises naturally in the study of fault tolerant linear arrays, (see [18]). The vertice ...
... What is the minimum possible number of vertices and edges of a graph G, such that even after removing all but E portion of its vertices or edges, the remaining graph still contains a path of length m? This problem arises naturally in the study of fault tolerant linear arrays, (see [18]). The vertice ...
Centrality
In graph theory and network analysis, indicators of centrality identify the most important vertices within a graph. Applications include identifying the most influential person(s) in a social network, key infrastructure nodes in the Internet or urban networks, and super-spreaders of disease. Centrality concepts were first developed in social network analysis, and many of the terms used to measure centrality reflect their sociological origin.They should not be confused with node influence metrics, which seek to quantify the influence of every node in the network.