1.3k citations · 2.2k across the 67 of their papers we have counts for
5 papers · 1 filter
Unifying Sparsest Cut, Cluster Deletion, and Modularity Clustering Objectives with Correlation Clustering
Nate Veldt, David Gleich, Anthony Wirth
Graph clustering, or community detection, is the task of identifying groups of closely related objects in a large network. In this paper we introduce a new community-detection fram…
Coin-flipping, ball-dropping, and grass-hopping for generating random graphs from matrices of edge probabilities
Arjun S. Ramani, Nicole Eikmeier, David F. Gleich
Common models for random graphs, such as Erdős-Rényi and Kronecker graphs, correspond to generating random adjacency matrices where each entry is non-zero based on a large matrix o…
Retrospective Higher-Order Markov Processes for User Trails
Tao Wu, David Gleich
Users form information trails as they browse the web, checkin with a geolocation, rate items, or consume media. A common problem is to predict what a user might do next for the pur…
Multimodal Network Alignment
Huda Nassar, David F. Gleich
A multimodal network encodes relationships between the same set of nodes in multiple settings, and network alignment is a powerful tool for transferring information and insight bet…
Deconvolving Feedback Loops in Recommender Systems
Ayan Sinha, David F. Gleich, Karthik Ramani
Collaborative filtering is a popular technique to infer users' preferences on new content based on the collective information of all users preferences. Recommender systems then use…