Generalization Error and Algorithmic Convergence of Median Boosting.
Balázs KéglPublished in: NIPS (2004)
Keyphrases
- generalization error
- training error
- boosting algorithms
- weak learners
- learning algorithm
- cross validation
- active learning
- classification error
- model selection
- upper bound
- training set
- binary classification
- linear classifiers
- sample complexity
- training data
- weak classifiers
- supervised learning
- sample size
- generalization error bounds
- target function
- convergence speed
- convergence rate
- conditional expectation
- learning machines
- adaboost algorithm
- subspace information criterion
- uniform convergence
- query by committee
- minimum margin
- gradient method
- error rate
- lower bound
- data sets
- learning rate
- loss function
- pairwise
- feature selection
- machine learning
- neural network