We introduce a maximum L<italic>q</italic>-likelihood estimation (ML<italic>q</italic>E) of mixture models using our proposed expectation-maximization (EM) algorithm, namely the EM algorithm with L<italic>q</italic>-likelihood (EM-L<italic>q</italic>). Properties of the ML<italic>q</italic>E obtained from the proposed EM-L<italic>q</italic> are studied through simulated mixture model data....

In this article we initiate the study of class cover catch digraphs, a special case of intersection digraphs motivated by applications in machine learning and statistical pattern recognition. Our main result is the exact distribution of the domination number for a data-driven model of random...

Fusion of information from graph features and content can provide superior inference for an anomaly detection task, compared to the corresponding content-only or graph feature-only statistics. In this paper, we design and execute an experiment on a time series of attributed graphs extracted from...

Many problems can be cast as statistical inference on an attributed random graph. Our motivation is change detection in communication graphs. We prove that tests based on a fusion of graph-derived and content-derived metadata can be more powerful than those based on graph or content features...