The Guedon-Vershynin Semi-definite Programming Approach to Low Dimensional Embedding for Unsupervised Clustering.
Stéphane ChrétienClément DombryAdrien FaivrePublished in: Frontiers Appl. Math. Stat. (2019)
Keyphrases
- unsupervised clustering
- semi definite programming
- low dimensional
- pairwise constraints
- semi supervised
- high dimensional
- pairwise
- dimensionality reduction
- kernel matrix
- supervised classification
- input space
- data points
- high dimensional data
- spectral clustering
- clustering method
- unlabeled data
- metric learning
- k means
- clustering algorithm
- image segmentation
- data representation
- decision boundary
- feature space
- semi supervised learning
- document clustering
- loss function
- principal component analysis
- distance metric
- labeled data
- image processing
- euclidean space
- class labels
- data clustering
- data sets
- unsupervised learning
- model selection
- feature extraction
- face recognition
- machine learning