Reconstruction and Decomposition of High-Dimensional Landscapes via Unsupervised Learning.
Jing LeiNasrin AkhterWanli QiaoAmarda ShehuPublished in: KDD (2020)
Keyphrases
- unsupervised learning
- high dimensional
- dimensionality reduction
- sparse coding
- supervised learning
- reconstruction error
- low dimensional
- high dimensional data
- semi supervised
- deep learning
- high dimensionality
- feature space
- parameter space
- similarity search
- machine learning
- data points
- discrete tomography
- sparse data
- variable selection
- manifold learning
- decision trees
- model selection
- high resolution
- nearest neighbor
- three dimensional
- image reconstruction
- decomposition methods
- feature selection
- data mining
- metric space
- object recognition
- compressed sensing
- reconstruction method
- high dimensional spaces
- compressive sensing
- reconstructed image
- reconstruction process
- decomposition method
- principal component analysis
- genetic algorithm
- pairwise
- computer vision
- microarray data
- reinforcement learning