| No. |
Title |
Author |
Year |
| 1 |
Learning in the context of very high dimensional data (Dagstuhl Seminar 11341) |
Biehl, Michael et al. |
2011 |
| 2 |
10302 Abstracts Collection -- Learning paradigms in dynamic environments |
Hammer, Barbara et al. |
2010 |
| 3 |
10302 Summary -- Learning paradigms in dynamic environments |
Hammer, Barbara et al. |
2010 |
| 4 |
Some steps towards a general principle for dimensionality reduction mappings |
Hammer, Barbara et al. |
2010 |
| 5 |
09081 Abstracts Collection -- Similarity-based learning on structures |
Biehl, Michael et al. |
2009 |
| 6 |
09081 Summary -- Similarity-based learning on structures |
Biehl, Michael et al. |
2009 |
| 7 |
08041 Abstracts Collection -- Recurrent Neural Networks - Models, Capacities, and Applications |
De Raedt, Luc et al. |
2008 |
| 8 |
08041 Summary -- Recurrent Neural Networks - Models, Capacities, and Applications |
De Raedt, Luc et al. |
2008 |
| 9 |
A general framework for unsupervised preocessing of structured data |
Hammer, Barbara et al. |
2008 |
| 10 |
07131 Abstracts Collection -- Similarity-based Clustering and its Application to Medicine and Biology |
Biehl, Michael et al. |
2007 |
| 11 |
07131 Summary -- Similarity-based Clustering and its Application to Medicine and Biology |
Biehl, Michael et al. |
2007 |
| 12 |
Learning Vector Quantization: generalization ability and dynamics of competing prototypes |
Witoelar, Aree et al. |
2007 |
| 13 |
Relational Clustering |
Hammer, Barbara et al. |
2007 |
