Villmann T, Haase S, Schleif F-M, Hammer B. Divergence Based Online Learning in Vector Quantization. In: Rutkowski L, Scherer R, Tadeusiewicz R, Zadeh L, Zurada J, eds. Artificial Intelligence and Soft Computing. Lecture Notes in Computer Science, 6113. Berlin, Heidelberg: Springer; 2010: 479-486
Hammer B, Strickert M, Villmann T. Learning Vector Quantization for Multimodal Data. In: Dorronsoro ...
Biehl M, Gosh A, Hammer B. The dynamics of Learning Vector Quantization. In: Verleysen M, ed. ESANN'...
Fischer L, Hammer B, Wersing H. Rejection strategies for learning vector quantization. In: Verleysen...
Villmann T, Haase S, Schleif F-M, Hammer B, Biehl M. The Mathematics of Divergence Based Online Lear...
Mwebaze E, Schneider P, Schleif F-M, Haase S, Villmann T, Biehl M. Divergence based Learning Vector ...
We propose the utilization of divergences in gradient descent learning of supervised and unsupervise...
Mwebaze E, Schneider P, Schleif F-M, et al. Divergence based classification in Learning Vector Quant...
We propose relevance learning for unsupervised online vector quantization algorithm based on stochas...
We discuss the use of divergences in dissimilarity-based classification. Divergences can be employed...
Hammer B, Hofmann D, Schleif F-M, Zhu X. Learning vector quantization for (dis-)similarities. NeuroC...
Schneider P, Biehl M, Hammer B. Distance learning in discriminative vector quantization. Neural Comp...
Learning vector quantization (LVQ) is one of the most powerful approaches for prototype based classi...
Biehl M, Ghosh A, Hammer B. Learning vector quantization: The dynamics of winner-takes-all algorithm...
Fischer L, Nebel D, Villmann T, Hammer B, Wersing H. Rejection Strategies for Learning Vector Quanti...
Dit proefschrift geeft een systematische analyse van op divergentie gebaseerde leer algoritmen en le...
Hammer B, Strickert M, Villmann T. Learning Vector Quantization for Multimodal Data. In: Dorronsoro ...
Biehl M, Gosh A, Hammer B. The dynamics of Learning Vector Quantization. In: Verleysen M, ed. ESANN'...
Fischer L, Hammer B, Wersing H. Rejection strategies for learning vector quantization. In: Verleysen...
Villmann T, Haase S, Schleif F-M, Hammer B, Biehl M. The Mathematics of Divergence Based Online Lear...
Mwebaze E, Schneider P, Schleif F-M, Haase S, Villmann T, Biehl M. Divergence based Learning Vector ...
We propose the utilization of divergences in gradient descent learning of supervised and unsupervise...
Mwebaze E, Schneider P, Schleif F-M, et al. Divergence based classification in Learning Vector Quant...
We propose relevance learning for unsupervised online vector quantization algorithm based on stochas...
We discuss the use of divergences in dissimilarity-based classification. Divergences can be employed...
Hammer B, Hofmann D, Schleif F-M, Zhu X. Learning vector quantization for (dis-)similarities. NeuroC...
Schneider P, Biehl M, Hammer B. Distance learning in discriminative vector quantization. Neural Comp...
Learning vector quantization (LVQ) is one of the most powerful approaches for prototype based classi...
Biehl M, Ghosh A, Hammer B. Learning vector quantization: The dynamics of winner-takes-all algorithm...
Fischer L, Nebel D, Villmann T, Hammer B, Wersing H. Rejection Strategies for Learning Vector Quanti...
Dit proefschrift geeft een systematische analyse van op divergentie gebaseerde leer algoritmen en le...
Hammer B, Strickert M, Villmann T. Learning Vector Quantization for Multimodal Data. In: Dorronsoro ...
Biehl M, Gosh A, Hammer B. The dynamics of Learning Vector Quantization. In: Verleysen M, ed. ESANN'...
Fischer L, Hammer B, Wersing H. Rejection strategies for learning vector quantization. In: Verleysen...