Dimensionality Reduction for Representing the Knowledge of Probabilistic Models.
Marc T. LawJake SnellAmir-massoud FarahmandRaquel UrtasunRichard S. ZemelPublished in: ICLR (Poster) (2019)
Keyphrases
- probabilistic model
- dimensionality reduction
- graphical models
- knowledge acquisition
- knowledge extraction
- data representation
- conditional random fields
- domain knowledge
- knowledge discovery
- knowledge base
- hidden variables
- learning systems
- high dimensional data
- knowledge management
- knowledge representation
- high dimensional
- feature space
- pattern recognition
- feature extraction
- data mining techniques
- data points
- generative model
- kernel function
- latent variables
- bayesian networks
- data sets
- formal representation
- structure preserving
- pattern recognition and machine learning