From Probabilistic Graphical Models to Generalized Tensor Networks for Supervised Learning.
Ivan GlasserNicola PancottiJ. Ignacio CiracPublished in: IEEE Access (2020)
Keyphrases
- probabilistic graphical models
- supervised learning
- graphical models
- markov networks
- first order logic
- social networks
- probabilistic inference
- higher order
- belief propagation
- machine learning
- approximate inference
- network structure
- random variables
- dimensionality reduction
- probabilistic model
- training set
- maximum likelihood
- latent variables
- probability distribution
- parameter learning
- exact inference
- learning algorithm