433 citations · 1.3k across the 96 of their papers we have counts for
9 papers · 1 filter
When not to target negative ties? Studying competitive influence maximisation in signed networks
Sukankana Chakraborty, Markus Brede, Sebastian Stein +1
We explore the influence maximisation problem in networks with negative ties. Where prior work has focused on unsigned networks, we investigate the need to consider negative ties i…
Deep Demixing: Reconstructing the Evolution of Network Epidemics
Boning Li, Gojko Čutura, Ananthram Swami +1
We propose the deep demixing (DDmix) model, a graph autoencoder that can reconstruct epidemics evolving over networks from partial or aggregated temporal information. Assuming know…
CARL: Content-Aware Representation Learning for Heterogeneous Networks
Chuxu Zhang, Ananthram Swami, Nitesh V. Chawla
Heterogeneous networks not only present a challenge of heterogeneity in the types of nodes and relations, but also the attributes and content associated with the nodes. While recen…
An efficient alternative to Ollivier-Ricci curvature based on the Jaccard metric
Siddharth Pal, Feng Yu, Terrence J. Moore +3
We study Ollivier-Ricci curvature, a discrete version of Ricci curvature, which has gained popularity over the past several years and has found applications in diverse fields. Howe…
Spectral Algorithms for Temporal Graph Cuts
Arlei Silva, Ambuj Singh, Ananthram Swami
The sparsest cut problem consists of identifying a small set of edges that breaks the graph into balanced sets of vertices. The normalized cut problem balances the total degree, in…
Maximizing Coverage Centrality via Network Design: Extended Version
Sourav Medya, Arlei Silva, Ambuj Singh +2
Network centrality plays an important role in many applications. Central nodes in social networks can be influential, driving opinions and spreading news or rumors.In hyperlinked e…
Temporal Clustering in Dynamic Networks with Tensor Decomposition
Kun Tu, Bruno Ribeiro, Ananthram Swami +1
Dynamic networks are increasingly being usedd to model real world datasets. A challenging task in their analysis is to detect and characterize clusters. It is useful for analyzing…
Node Dominance: Revealing Community and Core-Periphery Structure in Social Networks
Jennifer Gamble, Harish Chintakunta, Adam Wilkerson +2
This study relates the local property of node dominance to local and global properties of a network. Iterative removal of dominated nodes yields a distributed algorithm for computi…
Minimum Information Dominating Set for Opinion Sampling
Jianhang Gao, Qing Zhao, Anathram Swami
We consider the problem of inferring the opinions of a social network through strategically sampling a minimum subset of nodes by exploiting correlations in node opinions. We first…