Neural mixture models with expectation-maximization for end-to-end deep clustering.
Dumindu TisseraKasun VithanageRukshan WijesingheAlex XavierSanath JayasenaSubha FernandoRanga RodrigoPublished in: Neurocomputing (2022)
Keyphrases
- end to end
- mixture model
- expectation maximization
- em algorithm
- k means
- unsupervised learning
- model based clustering
- finite mixture models
- density estimation
- mixture modeling
- gaussian mixture model
- overlapping clustering
- generative model
- probabilistic model
- maximum likelihood
- finite mixture model
- bayesian information criterion
- clustering algorithm
- network architecture
- clustering method
- congestion control
- probability density function
- minimum message length
- gaussian mixture
- admission control
- model selection
- image segmentation
- cluster analysis
- transport layer
- image processing
- hierarchical clustering
- dirichlet distribution
- finite mixtures
- computer vision
- text localization and recognition
- mixture components
- document clustering
- outlier detection
- missing data
- semi supervised