Toward L_∞Recovery of Nonlinear Functions: A Polynomial Sample Complexity Bound for Gaussian Random Fields.
Kefan DongTengyu MaPublished in: COLT (2023)
Keyphrases
- nonlinear functions
- random fields
- sample complexity
- upper bound
- vc dimension
- lower bound
- rbf network
- input output
- markov random field
- maximum entropy
- theoretical analysis
- learning algorithm
- nonlinear systems
- non stationary
- active learning
- neural network
- conditional random fields
- learning problems
- generalization error
- special case
- supervised learning
- parameter estimation
- basis functions
- probabilistic model
- sample size
- worst case
- training examples
- data sets
- least squares
- rbf neural network
- radial basis function
- higher order
- optimal solution
- image processing
- machine learning
- maximum likelihood