Hofmann, Daniela: Learning vector quantization for proximity data. 2016
Inhalt
- Introduction
- Vectorial learning vector quantization
- Learning vector quantization
- Generalized learning vector quantization
- Robust soft learning vector quantization
- Abstract formulation
- Discussion
- LVQ for proximities
- General view
- Optimization concerning the coefficients
- Optimization concerning the prototypes
- Characteristics of the methods
- Transferability of the mathematical background
- Techniques to enforce that data are Euclidean
- Experiments
- Discussion
- Efficiency
- Nyström approximation of the Gram matrix
- Nyström approximation for LVQ
- Quick check
- Experiments
- Discussion
- Interpretability
- Approximation of the prototypes
- Sparse training
- Simple heuristic approximations of the prototypes
- Approximate representations of the prototypes
- Characteristics of the techniques
- Experiments
- Discussion
- Conclusions