Quadratic Problem Formulation with Linear Constraints for Normalized Cut Clustering.
Diego Hernán Peluffo-OrdóñezCristian Castro HoyosCarlos Daniel Acosta-MedinaGermán Castellanos-DomínguezPublished in: CIARP (2014)
Keyphrases
- linear constraints
- spectral relaxation
- normalized cut
- quadratic program
- spectral clustering
- linearly constrained
- graph partitioning
- image segmentation
- k means
- clustering algorithm
- semi definite programming
- graph clustering
- objective function
- similarity graph
- clustering method
- mean shift
- graph cuts
- data clustering
- highly correlated
- nonnegative matrix factorization
- graphical models
- weighted graph
- graph model
- convex optimization
- variational inequalities
- graph structure
- computer vision
- directed graph
- cluster analysis
- statistically significant
- pairwise
- image processing