Convolutional 2D LDA for Nonlinear Dimensionality Reduction.
Qi WangZequn QinFeiping NieYuan YuanPublished in: IJCAI (2017)
Keyphrases
- nonlinear dimensionality reduction
- dimensionality reduction
- linear discriminant analysis
- high dimensional data
- manifold learning
- dimensionality reduction methods
- latent dirichlet allocation
- discriminant analysis
- low dimensional
- locally linear embedding
- principal component analysis
- face recognition
- dimension reduction
- high dimensional
- feature extraction
- topic models
- high dimensionality
- maximum variance unfolding
- generative model
- data points
- pattern recognition
- sparse coding
- principal components analysis
- subspace methods
- feature selection
- data sets
- feature space
- subspace learning
- principal components
- metric learning
- preprocessing step
- sparse representation
- euclidean distance
- semi supervised
- data analysis
- support vector
- learning algorithm
- neural network