Pivot Selection for Dimension Reduction using Annealing by Increasing Resampling.
Yasunobu ImamuraNaoya HiguchiTetsuji KuboyamaKouichi HirataTakeshi ShinoharaPublished in: LWDA (2017)
Keyphrases
- dimension reduction
- principal component analysis
- feature extraction
- variable selection
- low dimensional
- high dimensional problems
- high dimensional
- data mining and machine learning
- singular value decomposition
- unsupervised learning
- linear discriminant analysis
- random projections
- manifold learning
- high dimensionality
- high dimensional data
- feature selection
- dimensionality reduction
- simulated annealing
- feature space
- dimension reduction methods
- computer vision
- partial least squares
- discriminative information
- high dimensional data analysis
- cluster analysis
- manifold embedding
- discriminant analysis
- k nearest neighbor
- model selection
- probabilistic model
- feature vectors
- preprocessing
- data analysis
- image segmentation
- learning algorithm
- sparse metric learning