Approximate Inference via Weighted Rademacher Complexity.
Jonathan KuckAshish SabharwalStefano ErmonPublished in: CoRR (2018)
Keyphrases
- approximate inference
- rademacher complexity
- graphical models
- belief propagation
- probabilistic inference
- data dependent
- parameter estimation
- gaussian process
- message passing
- bayesian networks
- risk bounds
- latent variables
- conditional random fields
- dynamic bayesian networks
- generalization error
- probabilistic model
- least squares
- image processing
- machine learning
- multi view
- markov random field