Unifying Variational Inference and PAC-Bayes for Supervised Learning that Scales.
Sanjay ThakurHerke van HoofGunshi GuptaDavid MegerPublished in: CoRR (2019)
Keyphrases
- variational inference
- supervised learning
- pac bayes
- bayesian inference
- posterior distribution
- topic models
- gaussian process
- mixture model
- probabilistic model
- variational methods
- unsupervised learning
- latent dirichlet allocation
- closed form
- exponential family
- semi supervised
- training data
- reinforcement learning
- active learning
- learning problems
- semi supervised learning
- training set
- machine learning
- hyperparameters
- statistical learning
- labeled data
- approximate inference
- parameter estimation
- pairwise
- learning algorithm
- probabilistic inference
- generative model
- text mining