d Abstract) Colin Cooper∗ , Martin Dyer† and Catherine Greenhill‡ We consider a simple Markov chain for d-regular graphs on n vertices, and show that the mixing time of this...
Colin Cooper, Martin E. Dyer, Catherine S. Greenhi...
Understanding the graph structure of the Internet is a crucial step for building accurate network models and designing efficient algorithms for Internet applications. Yet, obtaini...
Dimitris Achlioptas, Aaron Clauset, David Kempe, C...
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
Estimating characteristics of large graphs via sampling is a vital part of the study of complex networks. Current sampling methods such as (independent) random vertex and random w...
We analyze dependencies in power law graph data (Web sample, Wikipedia sample and a preferential attachment graph) using statistical inference for multivariate regular variation. ...