118 citations · 346 across the 23 of their papers we have counts for
5 papers · 1 filter
Multiple Network Embedding for Anomaly Detection in Time Series of Graphs
Guodong Chen, Jesús Arroyo, Avanti Athreya +7
This paper considers the graph signal processing problem of anomaly detection in time series of graphs. We examine two related, complementary inference tasks: the detection of anom…
The Importance of Being Correlated: Implications of Dependence in Joint Spectral Inference across Multiple Networks
Konstantinos Pantazis, Avanti Athreya, Jesús Arroyo +3
Spectral inference on multiple networks is a rapidly-developing subfield of graph statistics. Recent work has demonstrated that joint, or simultaneous, spectral embedding of multip…
On spectral algorithms for community detection in stochastic blockmodel graphs with vertex covariates
Cong Mu, Angelo Mele, Lingxin Hao +3
In network inference applications, it is often desirable to detect community structure, namely to cluster vertices into groups, or blocks, according to some measure of similarity.…
Distance-based Positive and Unlabeled Learning for Ranking
Hayden S. Helm, Amitabh Basu, Avanti Athreya +12
Learning to rank -- producing a ranked list of items specific to a query and with respect to a set of supervisory items -- is a problem of general interest. The setting we consider…
On a complete and sufficient statistic for the correlated Bernoulli random graph model
Donniell E. Fishkind, Avanti Athreya, Lingyao Meng +2
Inference on vertex-aligned graphs is of wide theoretical and practical importance.There are, however, few flexible and tractable statistical models for correlated graphs, and even…