An Information-theoretic Learning Algorithm for Neural Network Classification.
David J. MillerAjit V. RaoKenneth RoseAllen GershoPublished in: NIPS (1995)
Keyphrases
- information theoretic
- neural network
- mutual information
- information theory
- learning algorithm
- theoretic framework
- back propagation
- pattern recognition
- feature vectors
- jensen shannon divergence
- machine learning algorithms
- training samples
- feature selection
- multi modality
- supervised learning
- information bottleneck
- competitive learning
- machine learning
- entropy measure
- log likelihood
- information theoretic measures
- bregman divergences
- artificial neural networks
- classification accuracy
- support vector machine
- decision trees
- feature space
- feature extraction
- machine learning methods
- minimum description length
- kullback leibler divergence
- image classification
- training data
- computational learning theory
- cost sensitive
- active learning
- training set
- learning problems
- computer vision
- self organizing maps