Nonparametric Divergence Estimation with Applications to Machine Learning on Distributions.
Barnabás PóczosLiang XiongJeff G. SchneiderPublished in: UAI (2011)
Keyphrases
- machine learning
- nonparametric regression
- kullback leibler
- density estimation
- kl divergence
- parametric models
- probability density
- data driven
- parzen window
- kernel density estimation
- machine learning algorithms
- knowledge acquisition
- probability distribution
- decision trees
- learning systems
- accurate estimation
- estimation accuracy
- data mining
- nonparametric density estimation
- computer science
- information extraction
- transfer learning
- learning algorithm
- feature selection
- active learning
- kullback leibler divergence
- machine learning approaches
- estimation algorithm
- text classification
- statistical methods
- learning tasks
- parameter estimation
- kernel density
- computer vision
- bayesian approaches
- machine learning methods
- density estimates
- pattern recognition
- estimation error
- exponential family
- inductive logic programming
- knowledge representation
- inductive learning
- supervised learning
- maximum likelihood estimation
- text mining