Nonlinear Dimension Reduction with Kernel Sliced Inverse Regression.
Yi-Ren YehSu-Yun HuangYuh-Jye LeePublished in: IEEE Trans. Knowl. Data Eng. (2009)
Keyphrases
- nonlinear dimension reduction
- kernel ridge regression
- reproducing kernel hilbert space
- gaussian processes
- sparse kernel
- classification and regression problems
- kernel regression
- regression model
- kernel methods
- support vector
- regression method
- kernel function
- relevance vector machine
- gaussian process regression
- regression problems
- manifold learning
- support vector regression
- kernel partial least squares
- linear regression
- regression algorithm
- ridge regression
- model selection
- mercer kernels
- partial least squares
- kernel matrix
- gradient boosting
- loss function
- hilbert schmidt independence criterion
- regression methods
- input space
- computer vision
- machine learning