… First we sample reciprocal edges and based on these edges, we sample directed edges.
Our … not guarantee unbiased graph generation. That is, there is no guarantee that all random …

… sample graphs (or subgraphs), which can be taken from the given population graph by means
of the relevant known sampling … By default, a graph is directed, or a digraph, in this book. …

… To accurately estimate the degree and clique structures in large graphs with samples obtained
… MHRW [16], [17] was proposed to address SRW’s problem of being biased to nodes with …

… biased nature of ModDFS, In the second phase, we remove the extra edges from the sample
graph … graph properties on directed graphs using large-scale social network datasets. The …

… snowball samples) remains, particularly for directed networks where snowball sampling is
not … ERGM canonical parameters is biased precisely because it is unbiased by construction in …

… In order to create the test set, we randomly sample 10% of the nodes on each graph. We
plot the average precision corresponding to different values of k in Figure 4. The results show …

… attribute distributions in the original graph are well represented in the sample. Sampling the
graph uniformly at random works well to provide an unbiased estimate of the attribute value …

… In the algorithm study, we plan to properly modify MCGS to extend its applied scope from
undirected graphs to directed graphs or from scale-free graphs to other types of …

… , some sampling methods could get real network graphs easily, … FastSGG generates directed
and heterogeneous graph G = (V,E)… of a graph by learning the distribution of biased random …

… It is a directed acyclic graph G = {N, E}, indicating how a set of … the causal graph, we first
revisit the conventional biased SGG … were up-sampled by the inversed sample fraction during …