Correction to: On Orthogonal Projections for Dimension Reduction and Applications in Augmented Target Loss Functions for Learning Problems.
Anna BregerJosé Ignacio OrlandoPavol HarárMonika DörflerSophie KlimschaChristoph GrechenigBianca S. GerendasUrsula Schmidt-ErfurthMartin EhlerPublished in: J. Math. Imaging Vis. (2020)
Keyphrases
- dimension reduction
- learning problems
- loss function
- reproducing kernel hilbert space
- learning models
- supervised learning
- kernel methods
- learning tasks
- support vector
- high dimensional
- feature extraction
- learning algorithm
- principal component analysis
- binary classification
- pairwise
- singular value decomposition
- machine learning algorithms
- low dimensional
- high dimensional data
- machine learning
- random projections
- feature space
- feature selection
- linear discriminant analysis
- unsupervised learning
- dimensionality reduction
- semi supervised learning
- cluster analysis
- reinforcement learning
- high dimensionality
- image processing
- multi task
- image classification
- text classification
- data mining
- pairwise constraints
- face recognition
- training data
- active learning
- support vector machine
- semi supervised
- markov random field
- input data