A unifying approach to hard and probabilistic clustering

Keyphrases

• Completely Positive Factorization 100%
• Hard Clustering 100%
• Probabilistic Clustering 100%
• Multi-class 50%
• First-principles 50%
• Label Information 50%
• Spectral Clustering 50%
• Normalized Cut 50%
• Affinity Matrix 50%
• Clustering Problem 50%
• Algebraic Problems 50%
• K-means 50%
• Partial Labels 50%
• Clustering Scheme 50%
• Clustering Results 50%
• Doubly Stochastic 50%
• Class Clustering 50%
• Stochastic Constraints 50%

Computer Science

• Approximation (Algorithm) 100%
• Efficient Algorithm 100%
• Spectral Clustering 100%
• Affinity Matrix 100%
• Clustering Scheme 100%
• Clustering Result 100%