On the Parallelization of MCMC for Community Detection

Author:

Wanye Frank1,Gleyzer Vitaliy2,Kao Edward2,Feng Wu-chun1

Affiliation:

1. Virginia Tech, United States of America

2. MIT Lincoln Laboratory, United States of America

Funder

NSF Center for Space, High-performance, and Resilient Computing (SHREC)

Publisher

ACM

Reference24 articles.

1. A Random Graph Model for Power Law Graphs

2. Assessing the relevance of node features for network structure

3. The university of Florida sparse matrix collection

4. Christopher De Sa , Kunle Olukotun , and Christopher Ré . 2016 . Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling. IJCAI International Joint Conference on Artificial Intelligence 0 (2 2016), 4811–4815. https://doi.org/10.48550/arxiv.1602.07415 10.48550/arxiv.1602.07415 Christopher De Sa, Kunle Olukotun, and Christopher Ré. 2016. Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling. IJCAI International Joint Conference on Artificial Intelligence 0 (2 2016), 4811–4815. https://doi.org/10.48550/arxiv.1602.07415

5. Finding Protein Binding Sites Using Volunteer Computing Grids. Advances in Intelligent and Soft Computing 144 AISC;Desell Travis;VOL.,2012

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