Neural network learning algorithms for tracking minor subspace in high-dimensional data stream.
Da-Zheng FengWei Xing ZhengYing JiaPublished in: IEEE Trans. Neural Networks (2005)
Keyphrases
- high dimensional
- neural network
- data streams
- low dimensional
- learning algorithm
- back propagation
- dimensionality reduction
- high dimensional data
- feature space
- subspace learning
- change detection
- sliding window
- particle filter
- training samples
- lower dimensional
- fuzzy logic
- high dimensionality
- training data
- nearest neighbor
- neural network model
- training algorithm
- machine learning algorithms
- pattern recognition
- subspace clustering
- similarity search
- real time
- feature extraction
- manifold learning
- appearance model
- streaming data
- transactional data
- linear subspace
- parameter space
- rbf network
- artificial neural networks
- kalman filter
- data points
- multi dimensional
- machine learning
- kernel function
- continuous queries
- mean shift
- object tracking
- outlier detection
- learning tasks
- principal components
- principal component analysis
- supervised learning
- data distribution
- stream data
- learning problems