SeeM: A Shared Latent Variable Model for Unsupervised Multi-view Anomaly Detection.
Phuong NguyenTuan M. V. LePublished in: PAKDD (1) (2024)
Keyphrases
- multi view
- anomaly detection
- latent variable models
- semi supervised
- unsupervised learning
- latent variables
- d objects
- three dimensional
- semi supervised learning
- hidden markov models
- supervised learning
- probabilistic model
- data mining
- latent dirichlet allocation
- labeled data
- manifold learning
- expectation maximization
- hidden variables
- information retrieval
- decision trees
- active learning
- pairwise