Model-based kernel sum rule: kernel Bayesian inference with probabilistic models.
Yu NishiyamaMotonobu KanagawaArthur GrettonKenji FukumizuPublished in: Mach. Learn. (2020)
Keyphrases
- bayesian inference
- probabilistic model
- hidden variables
- kernel function
- hyperparameters
- kernel methods
- probabilistic modeling
- bayesian model
- prior information
- mixture model
- graphical models
- feature space
- inference process
- language model
- expectation maximization
- conditional random fields
- statistical inference
- weighted model counting
- markov networks
- variational inference
- variational bayes
- bayesian networks
- generative model
- support vector
- gaussian processes
- conditional probabilities
- hierarchical bayesian
- gaussian process
- latent variables
- particle filter
- hidden markov models
- objective function
- reinforcement learning