KAM Theory Meets Statistical Learning Theory: Hamiltonian Neural Networks with Non-zero Training Loss.
Yuhan ChenTakashi MatsubaraTakaharu YaguchiPublished in: AAAI (2022)
Keyphrases
- statistical learning theory
- neural network
- theoretical framework
- support vector machine
- statistical learning
- training process
- training algorithm
- machine learning
- supervised classification
- learning problems
- kernel machines
- empirical risk minimization
- vc dimension
- inductive inference
- supervised learning
- pattern recognition
- back propagation
- active learning
- granular computing
- training data
- multi class
- training set
- data sets
- fuzzy logic
- feature space
- artificial neural networks
- information theory
- training examples
- feature vectors
- unsupervised learning
- computational intelligence