47 citations · 111 across the 9 of their papers we have counts for
5 papers · 1 filter
Network Structure Inference, A Survey: Motivations, Methods, and Applications
Ivan Brugere, Brian Gallagher, Tanya Y. Berger-Wolf
Networks represent relationships between entities in many complex systems, spanning from online social interactions to biological cell development and brain connectivity. In many c…
MaxOutProbe: An Algorithm for Increasing the Size of Partially Observed Networks
Sucheta Soundarajan, Tina Eliassi-Rad, Brian Gallagher +1
Networked representations of real-world phenomena are often partially observed, which lead to incomplete networks. Analysis of such incomplete networks can lead to skewed results.…
Anomaly Detection in Dynamic Networks of Varying Size
Timothy La Fond, Jennifer Neville, Brian Gallagher
Dynamic networks, also called network streams, are an important data representation that applies to many real-world domains. Many sets of network data such as e-mail networks, soci…
Dynamic Behavioral Mixed-Membership Model for Large Evolving Networks
Ryan Rossi, Brian Gallagher, Jennifer Neville +1
The majority of real-world networks are dynamic and extremely large (e.g., Internet Traffic, Twitter, Facebook, ...). To understand the structural behavior of nodes in these large…
Role-Dynamics: Fast Mining of Large Dynamic Networks
Ryan Rossi, Brian Gallagher, Jennifer Neville +1
To understand the structural dynamics of a large-scale social, biological or technological network, it may be useful to discover behavioral roles representing the main connectivity…