A computationally efficient state-space partitioning approach to pricing high-dimensional American options via dimension reduction.
Xing JinXun LiHwee Huat TanZhenyu WuPublished in: Eur. J. Oper. Res. (2013)
Keyphrases
- dimension reduction
- high dimensional
- space partitioning
- computationally efficient
- high dimensional spaces
- low dimensional
- high dimensional problems
- high dimensionality
- similarity search
- high dimensional data
- principal component analysis
- manifold learning
- dimensionality reduction
- feature extraction
- feature space
- nearest neighbor
- unsupervised learning
- linear discriminant analysis
- singular value decomposition
- feature selection
- cluster analysis
- databases
- knowledge discovery
- data points
- preprocessing