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Random Subspace Mixture Models for Interpretable Anomaly Detection
We present a new subspace-based method to construct probabilistic models for high-dimensional data and highlight its use in anomaly detection.
Novel Edge and Density Metrics for Link Cohesion
We present a new metric of link cohesion for measuring the strength of edges in complex, highly connected graphs.
GALILEO: A Generalized Low-Entropy Mixture Model
We present a new method of generating mixture models for data with categorical attributes.
Bayesian Learning of Clique Tree Structure
The problem of categorical data analysis in high dimensions is considered.
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