Adaptive Graph Regularized Low-Rank Matrix Factorization With Noise and Outliers for Clustering.
Min ZhaoJinglei LiuPublished in: IEEE Access (2020)
Keyphrases
- missing data
- low rank matrix factorization
- arbitrary shape
- graph theoretic
- outlier detection
- graph clustering
- data points
- noisy data
- clustering algorithm
- clustering method
- k means
- cluster structure
- graph partitioning
- graph model
- missing values
- low rank
- solution path
- noise reduction
- matrix factorization
- graph mining
- spectral clustering
- graph layout
- normalized cut
- measurement error
- nearest neighbor
- high dimensional data
- learning algorithm