Probability Functional Descent: A Unifying Perspective on GANs, Variational Inference, and Reinforcement Learning.
Casey ChuJose H. BlanchetPeter W. GlynnPublished in: ICML (2019)
Keyphrases
- variational inference
- reinforcement learning
- bayesian inference
- posterior distribution
- probability distribution
- topic models
- probabilistic model
- probabilistic graphical models
- variational methods
- latent dirichlet allocation
- gaussian process
- approximate inference
- closed form
- mixture model
- exponential family
- exact inference
- dynamic programming
- factor graphs
- learning algorithm
- posterior probability
- latent variables
- generative model
- graphical models
- conditional probabilities
- feature selection
- machine learning
- hyperparameters
- belief propagation
- conditional random fields
- maximum likelihood
- image segmentation