Linearly-scalable learning of smooth low-dimensional patterns with permutation-aided entropic dimension reduction.
Illia HorenkoLukás PospísilPublished in: CoRR (2023)
Keyphrases
- dimension reduction
- low dimensional
- high dimensional
- manifold learning
- data mining and machine learning
- principal component analysis
- feature space
- unsupervised learning
- feature extraction
- reinforcement learning
- learning algorithm
- active learning
- random projections
- euclidean space
- high dimensional data
- dimensionality reduction
- learning process
- image processing
- preprocessing
- pattern recognition
- computer vision