On the Universal Clustering under a Broad Class of Loss Functions.
Vladimir NikulinPublished in: Int. J. Neural Syst. (2006)
Keyphrases
- loss function
- pairwise
- reproducing kernel hilbert space
- bregman divergences
- clustering algorithm
- loss minimization
- squared error
- pairwise constraints
- clustering method
- learning to rank
- support vector
- logistic regression
- spectral clustering
- convex loss functions
- risk minimization
- data clustering
- k means
- hinge loss
- update rules
- document clustering
- image segmentation