Fast Subspace Approximation via Greedy Least-Squares.
Mark A. IwenFelix KrahmerPublished in: CoRR (2013)
Keyphrases
- least squares
- set of basis functions
- search algorithm
- orthogonal matching pursuit
- greedy algorithm
- parameter estimation
- subspace clustering
- robust estimation
- feature selection
- feature space
- principal component analysis
- policy evaluation
- low dimensional
- data sets
- principal components
- error bounds
- sparse linear
- high dimensional data
- singular value decomposition
- search space
- high dimensional
- matrix approximation
- hill climbing
- subspace learning
- linear subspace
- approximation error
- subspace methods
- sparse approximation
- kernel based nonlinear
- levenberg marquardt
- sparse representation
- simulated annealing
- dynamic programming
- optical flow
- reinforcement learning
- feature extraction
- neural network