Variational inference for neural network matrix factorization and its application to stochastic blockmodeling.
Onno KampmanCreighton HeaukulaniPublished in: CoRR (2019)
Keyphrases
- matrix factorization
- variational inference
- bayesian inference
- topic models
- probabilistic graphical models
- collaborative filtering
- mixture model
- posterior distribution
- probabilistic model
- latent dirichlet allocation
- variational methods
- gaussian process
- recommender systems
- closed form
- exact inference
- missing data
- approximate inference
- graphical models
- exponential family
- factor graphs
- monte carlo
- belief networks
- probability distribution
- bayesian framework
- belief propagation
- message passing
- em algorithm
- expectation maximization