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Efficient Streaming Algorithms for Graphlet Sampling
Given a graph $ G $ and a positive integer $ k $, the Graphlet Sampling problem asks to
sample a connected induced $ k $-vertex subgraph of $ G $ uniformly at random. Graphlet …
sample a connected induced $ k $-vertex subgraph of $ G $ uniformly at random. Graphlet …
Fast and perfect sampling of subgraphs and polymer systems
We give an efficient perfect sampling algorithm for weighted, connected induced subgraphs
(or graphlets) of rooted, bounded degree graphs. Our algorithm utilizes a vertex-percolation …
(or graphlets) of rooted, bounded degree graphs. Our algorithm utilizes a vertex-percolation …
Estimating simplet counts via sampling
Simplicial complexes are higher-order combinatorial structures which have been used to
represent real-world complex systems. In this paper, we focus on the local patterns in …
represent real-world complex systems. In this paper, we focus on the local patterns in …
Faster motif counting via succinct color coding and adaptive sampling
We address the problem of computing the distribution of induced connected subgraphs, aka
graphlets or motifs, in large graphs. The current state-of-the-art algorithms estimate the motif …
graphlets or motifs, in large graphs. The current state-of-the-art algorithms estimate the motif …
Efficient and near-optimal algorithms for sampling small connected subgraphs
M Bressan - ACM Transactions on Algorithms, 2023 - dl.acm.org
We study the following problem: Given an integer k≥ 3 and a simple graph G, sample a
connected induced k-vertex subgraph of G uniformly at random. This is a fundamental graph …
connected induced k-vertex subgraph of G uniformly at random. This is a fundamental graph …
Efficient and near-optimal algorithms for sampling connected subgraphs
M Bressan - Proceedings of the 53rd Annual ACM SIGACT …, 2021 - dl.acm.org
We study the graphlet sampling problem: given an integer k≥ 3 and a graph G=(V, E),
sample a connected induced k-node subgraph of G (also called k-graphlet) uniformly at …
sample a connected induced k-node subgraph of G (also called k-graphlet) uniformly at …
Making mean-estimation more efficient using an MCMC trace variance approach: DynaMITE
We introduce a novel statistical measure for MCMC-mean estimation, the inter-trace
variance ${\rm trv}^{(\tau_ {rel})}({\cal M}, f) $, which depends on a Markov chain ${\cal M} …
variance ${\rm trv}^{(\tau_ {rel})}({\cal M}, f) $, which depends on a Markov chain ${\cal M} …
Demetris: counting (near)-cliques by crawling
We study the problem of approximately counting cliques and near cliques in a graph, where
the access to the graph is only available through crawling its vertices; thus typically seeing …
the access to the graph is only available through crawling its vertices; thus typically seeing …
Real-world networks are not always fast mixing
The mixing time of random walks on a graph has found broad applications across both
theoretical and practical aspects of computer science, with the application effects depending …
theoretical and practical aspects of computer science, with the application effects depending …
[PDF][PDF] The wedge picking model: A theoretical analysis of graph evolution caused by triadic closure and algorithmic implications
We theoretically analyze our model and show how to bound the growth rate of some
characteristics of the graph, such as degree of vertices. Leveraging our theoretical results …
characteristics of the graph, such as degree of vertices. Leveraging our theoretical results …