Bayesian Inference with Posterior Regularization and Infinite Latent Support Vector Machines
Jun ZhuNing ChenEric P. XingPublished in: CoRR (2012)
Keyphrases
- bayesian inference
- hyperparameters
- posterior distribution
- support vector
- regularization parameter
- probabilistic model
- prior information
- markov chain monte carlo
- gaussian process
- learning machines
- latent variables
- large margin classifiers
- bayesian model
- variational inference
- markov networks
- statistical inference
- gaussian processes
- variational bayes
- gibbs sampler
- kernel function
- hierarchical bayesian
- support vector machine
- generative model
- posterior probability
- hidden variables
- loss function
- regularization term
- cross validation
- reproducing kernel hilbert space
- bayesian networks
- probability distribution
- expectation propagation
- graphical models
- bayesian framework
- variational approximation
- bayesian models
- data sets
- maximum margin
- bayesian methods
- approximate inference
- particle filter
- expectation maximization
- kernel methods
- conditional random fields