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The optimization problem of finding such a set is called the maximum independent set problem. It is a strongly NP-hard problem. [3] As such, it is unlikely that there exists an efficient algorithm for finding a maximum independent set of a graph. Every maximum independent set also is maximal, but the converse implication does not necessarily hold.
For a graph = (,), an independent set is a maximal independent set if for , one of the following is true: [1] where () denotes the neighbors of The above can be restated as a vertex either belongs to the independent set or has at least one neighbor vertex that belongs to the independent set.
In graph theory and statistics, a graphon (also known as a graph limit) is a symmetric measurable function : [,] [,], that is important in the study of dense graphs. Graphons arise both as a natural notion for the limit of a sequence of dense graphs, and as the fundamental defining objects of exchangeable random graph models.
In this case, a single limit does not exist because the one-sided limits, and + exist and are finite, but are not equal: since, +, the limit does not exist. Then, x 0 {\displaystyle x_{0}} is called a jump discontinuity , step discontinuity , or discontinuity of the first kind .
An independent set of ⌊ ⌋ vertices (where ⌊ ⌋ is the floor function) in an n-vertex triangle-free graph is easy to find: either there is a vertex with at least ⌊ ⌋ neighbors (in which case those neighbors are an independent set) or all vertices have strictly less than ⌊ ⌋ neighbors (in which case any maximal independent set must have at least ⌊ ⌋ vertices). [4]
Informally, the hypergraph container lemma tells us that we can assign a small fingerprint to each independent set, so that all independent sets with the same fingerprint belong to the same larger set, = (), the associated container, that has size bounded away from the number of vertices of the hypergraph. Further, these fingerprints are small ...
(This is the Cesàro limit of the indicator functions. In cases where the Cesàro limit does not exist this function can actually be defined as the Banach limit of the indicator functions, which is an extension of this limit. This latter limit always exists for sums of indicator functions, so that the empirical distribution is always well-defined.)
The first three functions have points for which the limit does not exist, while the function = is not defined at =, but its limit does exist. respectively. If these limits exist at p and are equal there, then this can be referred to as the limit of f(x) at p. [7] If the one-sided limits exist at p, but are unequal, then there is no limit at ...