The Block Two-level Erdos Renyi (BTER) Graph Model
Abstract not provided.
Publications
Capturing Community Behavior in Very Large Networks
Abstract not provided.
Are we there yet? When to stop a Markov chain while generating random graphs
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Markov chains are convenient means of generating realizations of networks with a given (joint or otherwise) degree distribution, since they simply require a procedure for rewiring edges. The major challenge is to find the right number of steps to run such a chain, so that we generate truly independent samples. Theoretical bounds for mixing times of these Markov chains are too large to be practically useful. Practitioners have no useful guide for choosing the length, and tend to pick numbers fairly arbitrarily. We give a principled mathematical argument showing that it suffices for the length to be proportional to the number of desired number of edges. We also prescribe a method for choosing this proportionality constant. We run a series of experiments showing that the distributions of common graph properties converge in this time, providing empirical evidence for our claims. © 2012 Springer-Verlag.
Fast Triangle Counting through Wedge Sampling
Abstract not provided.
The Block Two-Level Erd&%23246s-R&%23233nyi (BTER) Graph Model
Abstract not provided.
Challenges in Streaming Graph Analysis
Abstract not provided.
How to make sense of massive real-world networks
Abstract not provided.
The degree relations of triangles in real-world networks and graph models
Abstract not provided.
Estimating a thinning ratio for a Markov chain of graphs
Abstract not provided.
The Inherent Community Structure in Real-World Graphs
Abstract not provided.
Generating independent graphs with prescribed joint degree distribution using a Markov chain sampler
Abstract not provided.
The BTER Graph Generator: A Scalable Model with Measurable Community Structure
Abstract not provided.
Scalable Methods for Characterizing and Generating Large Graphs
Abstract not provided.
The Block Two-Level Erdos-Renyi (BTER) Graph Model
Abstract not provided.
An In-Depth Study of Stochastic Kronecker Graphs
Journal of ACM
Abstract not provided.
The BTER Graph Model: Blocked Two-Level Erdos-Renyi
Abstract not provided.
Influence and Dynamic Behavior in Random Boolean Networks
Physical Review Letters
Abstract not provided.
A Hitchhiker's Guide to Choosing Parameters of Stochastic Kronecker Graphs
Abstract not provided.
Results 51–68 of 68