Krylov Subspace Recycling for Fast Iterative Least-Squares in Machine Learning.
Filip de RoosPhilipp HennigPublished in: CoRR (2017)
Keyphrases
- least squares
- machine learning
- machine learning algorithms
- learning algorithm
- parameter estimation
- machine learning methods
- data mining
- text classification
- computer science
- learning problems
- decision trees
- robust estimation
- machine learning approaches
- principal component analysis
- linear subspace
- singular value decomposition
- feature selection
- optical flow
- high dimensional
- feature space
- data analysis
- pattern recognition
- inductive learning
- model selection
- knowledge acquisition
- learning tasks
- low dimensional
- dimensionality reduction
- supervised learning
- information extraction
- levenberg marquardt
- neural network
- computer vision
- artificial intelligence
- iterative methods
- sparse linear
- kernel methods
- semi supervised learning
- computational intelligence
- text mining
- knowledge discovery
- knowledge representation
- active learning
- natural language