Convergence of a Grassmannian Gradient Descent Algorithm for Subspace Estimation From Undersampled Data.
Dejiao ZhangLaura BalzanoPublished in: CoRR (2016)
Keyphrases
- input data
- estimation algorithm
- objective function
- cost function
- data sets
- high dimensional data
- detection algorithm
- computational complexity
- estimation process
- synthetic datasets
- noisy data
- dynamic programming
- data structure
- learning algorithm
- optimal solution
- data analysis
- convergence rate
- expectation maximization
- data sources
- faster convergence
- particle swarm optimization
- preprocessing
- subspace clustering
- training data
- original data
- estimation accuracy
- decision trees
- learning rate
- principal components
- data mining
- image sequences
- similarity measure
- clustering method
- parameter estimation
- maximum likelihood
- data points
- probabilistic model
- np hard