Markov Chain Monte Carlo, Mixing, and the Spectral Gap
... MCMC is also useful when the posterior may not be complicated, but the number of variables is too large to be dealt with all at once. Random walks on very large graphs are an example of this. These sorts of graphs arise in internet-scale applications as representations of web pages or social network ...
... MCMC is also useful when the posterior may not be complicated, but the number of variables is too large to be dealt with all at once. Random walks on very large graphs are an example of this. These sorts of graphs arise in internet-scale applications as representations of web pages or social network ...
Dynamic coloring of graphs having no K5 minor
... minimum counterexamples, Lemmas 5 and 6, that are proved in Sections 3 and 4, respectively. In Section 5, we discuss a related question motivated by Hadwiger’s conjecture and prove Theorem 3. Notation: Let G be a graph. Let V (G) denote the set of vertices of G. Let E(G) denote the set of edges of G ...
... minimum counterexamples, Lemmas 5 and 6, that are proved in Sections 3 and 4, respectively. In Section 5, we discuss a related question motivated by Hadwiger’s conjecture and prove Theorem 3. Notation: Let G be a graph. Let V (G) denote the set of vertices of G. Let E(G) denote the set of edges of G ...
Graphs to semigroups
... • (Conjecture) Every transformation graph subsemigroup of TS(G) corresponds to a minor of G, and vice versa, every minor of G corresponds to a transformation graph subsemigroup of TS(G). • By ‘transformation graph subsemigroup’ we mean a subsemigroup which is isomorphic to a transformation graph sem ...
... • (Conjecture) Every transformation graph subsemigroup of TS(G) corresponds to a minor of G, and vice versa, every minor of G corresponds to a transformation graph subsemigroup of TS(G). • By ‘transformation graph subsemigroup’ we mean a subsemigroup which is isomorphic to a transformation graph sem ...
Chapter 14, Indexing Structures for Files
... ∗ All leaf nodes are at the same level. Leaf nodes have the same structure as internal nodes except that all of their tree pointers Pi are null. – What do we do if search key is nonkey in data file ? Keep a linked list of data pointers for each search value. – Insertion for B-Tree: Let p be the ord ...
... ∗ All leaf nodes are at the same level. Leaf nodes have the same structure as internal nodes except that all of their tree pointers Pi are null. – What do we do if search key is nonkey in data file ? Keep a linked list of data pointers for each search value. – Insertion for B-Tree: Let p be the ord ...
Generalized honeycomb torus
... Management, National Chiao Tung University, Hsinchu 30050, Taiwan, R.O.C. ...
... Management, National Chiao Tung University, Hsinchu 30050, Taiwan, R.O.C. ...
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... The network is divided into routing zones the zone is usually an sphere with a specified diameter, measured in hop counts the nodes positioned at the maximum distance from central node X are called peripheral nodes for the routing zone centered at X. When package needs to be sent from node A to ...
... The network is divided into routing zones the zone is usually an sphere with a specified diameter, measured in hop counts the nodes positioned at the maximum distance from central node X are called peripheral nodes for the routing zone centered at X. When package needs to be sent from node A to ...
Symmetric Splitting in the General Theory of Stable Models
... take F to be p ↔ q, with p as p and q as q. The graph DGpq [F ] in this case has two edges, from p to q and from q to p. The strongly connected component {p, q} of this graph has a common element with p and a common element with q, so that the splitting lemma is not applicable. Accordingly, the form ...
... take F to be p ↔ q, with p as p and q as q. The graph DGpq [F ] in this case has two edges, from p to q and from q to p. The strongly connected component {p, q} of this graph has a common element with p and a common element with q, so that the splitting lemma is not applicable. Accordingly, the form ...
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.